Methods for diagnosis and prognosis of renal injury and renal failure

ABSTRACT

The present invention relates to methods and compositions for monitoring subjects suffering from a renal injury. In particular, the invention relates to using assays that detect Beta-2-glycoprotein 1 as a prognostic biomarker in renal injuries.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No. 13/389,351 filed Apr. 9, 2012, now U.S. Pat. No. 8,871,459, issued Oct. 28, 2014, which is a United States national phase of International Application No. PCT/US2010/044772, filed Aug. 6, 2010, which designated the United States and which claims priority to U.S. Provisional Application No. 61/232,293, filed Aug. 7, 2009. The entire disclosure of all applications, including any drawings, is hereby incorporated by reference.

SEQUENCE LISTING

The instant application contains a Sequence Listing which has been submitted in ASCII format via EFS-Web and is hereby incorporated by reference in its entirety. Said ASCII copy, created on Oct. 27, 2014, is named AST15200CT_SeqListsing.txt and is 4 kilobytes in size.

BACKGROUND OF THE INVENTION

The following discussion of the background of the invention is merely provided to aid the reader in understanding the invention and is not admitted to describe or constitute prior art to the present invention.

The kidney is responsible for water and solute excretion from the body. Its functions include maintenance of acid-base balance, regulation of electrolyte concentrations, control of blood volume, and regulation of blood pressure. As such, loss of kidney function through injury and/or disease results in substantial morbidity and mortality. A detailed discussion of renal injuries is provided in Harrison's Principles of Internal Medicine, 17^(th) Ed., McGraw Hill, New York, pages 1741-1830, which are hereby incorporated by reference in their entirety. Renal disease and/or injury may be acute or chronic. Acute and chronic kidney disease are described as follows (from Current Medical Diagnosis & Treatment 2008, 47^(th) Ed, McGraw Hill, New York, pages 785-815, which are hereby incorporated by reference in their entirety): “Acute renal failure is worsening of renal function over hours to days, resulting in the retention of nitrogenous wastes (such as urea nitrogen) and creatinine in the blood. Retention of these substances is called azotemia. Chronic renal failure (chronic kidney disease) results from an abnormal loss of renal function over months to years”.

Acute renal failure (ARF, also known as acute kidney injury, or AKI) is an abrupt (typically detected within about 48 hours to 1 week) reduction in glomerular filtration. This loss of filtration capacity results in retention of nitrogenous (urea and creatinine) and non-nitrogenous waste products that are normally excreted by the kidney, a reduction in urine output, or both. It is reported that ARF complicates about 5% of hospital admissions, 4-15% of cardiopulmonary bypass surgeries, and up to 30% of intensive care admissions. ARF may be categorized as prerenal, intrinsic renal, or postrenal in causation. Intrinsic renal disease can be further divided into glomerular, tubular, interstitial, and vascular abnormalities. Major causes of ARF are described in the following table, which is adapted from the Merck Manual, 17^(th) ed., Chapter 222, and which is hereby incorporated by reference in their entirety:

Type Risk Factors Prerenal ECF volume depletion Excessive diuresis, hemorrhage, GI losses, loss of intravascular fluid into the extravascular space (due to ascites, peritonitis, pancreatitis, or burns), loss of skin and mucus membranes, renal salt- and water-wasting states Low cardiac output Cardiomyopathy, MI, cardiac tamponade, pulmonary embolism, pulmonary hypertension, positive-pressure mechanical ventilation Low systemic vascular Septic shock, liver failure, antihypertensive drugs resistance Increased renal vascular NSAIDs, cyclosporines, tacrolimus, hypercalcemia, resistance anaphylaxis, anesthetics, renal artery obstruction, renal vein thrombosis, sepsis, hepatorenal syndrome Decreased efferent ACE inhibitors or angiotensin II receptor blockers arteriolar tone (leading to decreased GFR from reduced glomerular transcapillary pressure, especially in patients with bilateral renal artery stenosis) Intrinsic Renal Acute tubular injury Ischemia (prolonged or severe prerenal state): surgery, hemorrhage, arterial or venous obstruction; Toxins: NSAIDs, cyclosporines, tacrolimus, aminoglycosides, foscarnet, ethylene glycol, hemoglobin, myoglobin, ifosfamide, heavy metals, methotrexate, radiopaque contrast agents, streptozotocin Acute glomerulonephritis ANCA-associated: Crescentic glomerulonephritis, polyarteritis nodosa, Wegener's granulomatosis; Anti- GBM glomerulonephritis: Goodpasture's syndrome; Immune-complex: Lupus glomerulonephritis, postinfectious glomerulonephritis, cryoglobulinemic glomerulonephritis Acute tubulointerstitial Drug reaction (eg, β-lactams, NSAIDs, sulfonamides, nephritis ciprofloxacin, thiazide diuretics, furosemide, phenytoin, allopurinol, pyelonephritis, papillary necrosis Acute vascular Vasculitis, malignant hypertension, thrombotic nephropathy microangiopathies, scleroderma, atheroembolism Infiltrative diseases Lymphoma, sarcoidosis, leukemia Postrenal Tubular precipitation Uric acid (tumor lysis), sulfonamides, triamterene, acyclovir, indinavir, methotrexate, ethylene glycol ingestion, myeloma protein, myoglobin Ureteral obstruction Intrinsic: Calculi, clots, sloughed renal tissue, fungus ball, edema, malignancy, congenital defects; Extrinsic: Malignancy, retroperitoneal fibrosis, ureteral trauma during surgery or high impact injury Bladder obstruction Mechanical: Benign prostatic hyperplasia, prostate cancer, bladder cancer, urethral strictures, phimosis, paraphimosis, urethral valves, obstructed indwelling urinary catheter; Neurogenic: Anticholinergic drugs, upper or lower motor neuron lesion

In the case of ischemic ARF, the course of the disease may be divided into four phases. During an initiation phase, which lasts hours to days, reduced perfusion of the kidney is evolving into injury. Glomerular ultrafiltration reduces, the flow of filtrate is reduced due to debris within the tubules, and back leakage of filtrate through injured epithelium occurs. Renal injury can be mediated during this phase by reperfusion of the kidney. Initiation is followed by an extension phase which is characterized by continued ischemic injury and inflammation and may involve endothelial damage and vascular congestion. During the maintenance phase, lasting from 1 to 2 weeks, renal cell injury occurs, and glomerular filtration and urine output reaches a minimum. A recovery phase can follow in which the renal epithelium is repaired and GFR gradually recovers. Despite this, the survival rate of subjects with ARF may be as low as about 60%.

Acute kidney injury caused by radiocontrast agents (also called contrast media) and other nephrotoxins such as cyclosporine, antibiotics including aminoglycosides and anticancer drugs such as cisplatin manifests over a period of days to about a week. Contrast induced nephropathy (CIN, which is AKI caused by radiocontrast agents) is thought to be caused by intrarenal vasoconstriction (leading to ischemic injury) and from the generation of reactive oxygen species that are directly toxic to renal tubular epithelial cells. CIN classically presents as an acute (onset within 24-48 h) but reversible (peak 3-5 days, resolution within 1 week) rise in blood urea nitrogen and serum creatinine.

A commonly reported criteria for defining and detecting AKI is an abrupt (typically within about 2-7 days or within a period of hospitalization) elevation of serum creatinine. Although the use of serum creatinine elevation to define and detect AKI is well established, the magnitude of the serum creatinine elevation and the time over which it is measured to define AKI varies considerably among publications. Traditionally, relatively large increases in serum creatinine such as 100%, 200%, an increase of at least 100% to a value over 2 mg/dL and other definitions were used to define AKI. However, the recent trend has been towards using smaller serum creatinine rises to define AKI. The relationship between serum creatinine rise, AKI and the associated health risks are reviewed in Praught and Shlipak, Curr Opin Nephrol Hypertens 14:265-270, 2005 and Chertow et al, J Am Soc Nephrol 16: 3365-3370, 2005, which, with the references listed therein, are hereby incorporated by reference in their entirety. As described in these publications, acute worsening renal function (AKI) and increased risk of death and other detrimental outcomes are now known to be associated with very small increases in serum creatinine. These increases may be determined as a relative (percent) value or a nominal value. Relative increases in serum creatinine as small as 20% from the pre-injury value have been reported to indicate acutely worsening renal function (AKI) and increased health risk, but the more commonly reported value to define AKI and increased health risk is a relative increase of at least 25%. Nominal increases as small as 0.3 mg/dL, 0.2 mg/dL or even 0.1 mg/dL have been reported to indicate worsening renal function and increased risk of death. Various time periods for the serum creatinine to rise to these threshold values have been used to define AKI, for example, ranging from 2 days, 3 days, 7 days, or a variable period defined as the time the patient is in the hospital or intensive care unit. These studies indicate there is not a particular threshold serum creatinine rise (or time period for the rise) for worsening renal function or AKI, but rather a continuous increase in risk with increasing magnitude of serum creatinine rise.

One study (Lassnigg et all, J Am Soc Nephrol 15:1597-1605, 2004, hereby incorporated by reference in its entirety) investigated both increases and decreases in serum creatinine. Patients with a mild fall in serum creatinine of −0.1 to −0.3 mg/dL following heart surgery had the lowest mortality rate. Patients with a larger fall in serum creatinine (more than or equal to −0.4 mg/dL) or any increase in serum creatinine had a larger mortality rate. These findings caused the authors to conclude that even very subtle changes in renal function (as detected by small creatinine changes within 48 hours of surgery) seriously effect patient's outcomes. In an effort to reach consensus on a unified classification system for using serum creatinine to define AKI in clinical trials and in clinical practice, Bellomo et al., Crit Care. 8(4):R204-12, 2004, which is hereby incorporated by reference in its entirety, proposes the following classifications for stratifying AKI patients:

-   “Risk”: serum creatinine increased 1.5 fold from baseline OR urine     production of <0.5 ml/kg body weight/hr for 6 hours; -   “Injury”: serum creatinine increased 2.0 fold from baseline OR urine     production <0.5 ml/kg/hr for 12 h; -   “Failure”: serum creatinine increased 3.0 fold from baseline OR     creatinine >355 μmol/l (with a rise of >44) or urine output below     0.3 ml/kg/hr for 24 h or anuria for at least 12 hours; -   And included two clinical outcomes: -   “Loss”: persistent need for renal replacement therapy for more than     four weeks. -   “ESRD”: end stage renal disease—the need for dialysis for more than     3 months. -   These criteria are called the RIFLE criteria, which provide a useful     clinical tool to classify renal status. As discussed in Kellum,     Crit. Care Med. 36: S141-45, 2008 and Ricci et al., Kidney Int. 73,     538-546, 2008, each hereby incorporated by reference in its     entirety, the RIFLE criteria provide a uniform definition of AKI     which has been validated in numerous studies.

More recently, Mehta et al., Crit. Care 11:R31 (doi:10.1186.cc5713), 2007, hereby incorporated by reference in its entirety, proposes the following similar classifications for stratifying AKI patients, which have been modified from RIFLE:

-   “Stage I”: increase in serum creatinine of more than or equal to 0.3     mg/dL (≧26.4 μmol/l) or increase to more than or equal to 150%     (1.5-fold) from baseline OR urine output less than 0.5 mL/kg per     hour for more than 6 hours; -   “Stage II”: increase in serum creatinine to more than 200% (>2-fold)     from baseline OR urine output less than 0.5 mL/kg per hour for more     than 12 hours; -   “Stage III”: increase in serum creatinine to more than 300%     (>3-fold) from baseline OR serum creatinine ≧354 μmol/L accompanied     by an acute increase of at least 44 μmol/L OR urine output less than     0.3 mL/kg per hour for 24 hours or anuria for 12 hours.

The CIN Consensus Working Panel (McCollough et al, Rev Cardiovasc Med. 2006; 7(4):177-197, hereby incorporated by reference in its entirety) uses a serum creatinine rise of 25% to define Contrast induced nephropathy (which is a type of AKI). Although various groups propose slightly different criteria for using serum creatinine to detect AKI, the consensus is that small changes in serum creatinine, such as 0.3 mg/dL or 25%, are sufficient to detect AKI (worsening renal function) and that the magnitude of the serum creatinine change is an indicator of the severity of the AKI and mortality risk.

Although serial measurement of serum creatinine over a period of days is an accepted method of detecting and diagnosing AKI and is considered one of the most important tools to evaluate AKI patients, serum creatinine is generally regarded to have several limitations in the diagnosis, assessment and monitoring of AKI patients. The time period for serum creatinine to rise to values (e.g., a 0.3 mg/dL or 25% rise) considered diagnostic for AKI can be 48 hours or longer depending on the definition used. Since cellular injury in AKI can occur over a period of hours, serum creatinine elevations detected at 48 hours or longer can be a late indicator of injury, and relying on serum creatinine can thus delay diagnosis of AKI. Furthermore, serum creatinine is not a good indicator of the exact kidney status and treatment needs during the most acute phases of AKI when kidney function is changing rapidly. Some patients with AKI will recover fully, some will need dialysis (either short term or long term) and some will have other detrimental outcomes including death, major adverse cardiac events and chronic kidney disease. Because serum creatinine is a marker of filtration rate, it does not differentiate between the causes of AKI (pre-renal, intrinsic renal, post-renal obstruction, atheroembolic, etc) or the category or location of injury in intrinsic renal disease (for example, tubular, glomerular or interstitial in origin). Urine output is similarly limited, Knowing these things can be of vital importance in managing and treating patients with AKI.

These limitations underscore the need for better methods to detect and assess AKI, particularly in the early and subclinical stages, but also in later stages when recovery and repair of the kidney can occur. Furthermore, there is a need to better identify patients who are at risk of having an AKI.

BRIEF SUMMARY OF THE INVENTION

It is an object of the invention to provide methods and compositions for evaluating renal function in a subject. As described herein, measurement of Beta-2-glycoprotein 1 (human precursor Swiss-Prot P02749, also known as Apolipoprotein H) can be used for diagnosis, prognosis, risk stratification, staging, monitoring, categorizing and determination of further diagnosis and treatment regimens in subjects suffering or at risk of suffering from an injury to renal function, reduced renal function, and/or acute renal failure (also called acute kidney injury).

This biomarker may be used for risk stratification (that is, to identify subjects at risk for a future injury to renal function, for future progression to reduced renal function, for future progression to ARF, for future improvement in renal function, etc.); for diagnosis of existing disease (that is, to identify subjects who have suffered an injury to renal function, who have progressed to reduced renal function, who have progressed to ARF, etc.); for monitoring for deterioration or improvement of renal function; and for predicting a future medical outcome, such as improved or worsening renal function, a decreased or increased mortality risk, a decreased or increased risk that a subject will require renal replacement therapy (i.e., hemodialysis, peritoneal dialysis, hemofiltration, and/or renal transplantation, a decreased or increased risk that a subject will recover from an injury to renal function, a decreased or increased risk that a subject will recover from ARF, a decreased or increased risk that a subject will progress to end stage renal disease, a decreased or increased risk that a subject will progress to chronic renal failure, a decreased or increased risk that a subject will suffer rejection of a transplanted kidney, etc.

In a first aspect, the present invention relates to methods for evaluating renal status in a subject. These methods comprise performing an assay method that is configured to detect Beta-2-glycoprotein 1 in a body fluid sample obtained from the subject. The assay result, for example a measured concentration of Beta-2-glycoprotein 1, is then correlated to the renal status of the subject. This correlation to renal status may include correlating the assay result to one or more of risk stratification, diagnosis, prognosis, staging, classifying and monitoring of the subject as described herein. Thus, the present invention utilizes Beta-2-glycoprotein 1 for the evaluation of renal injury.

In certain embodiments, the methods for evaluating renal status described herein are methods for risk stratification of the subject; that is, assigning a likelihood of one or more future changes in renal status to the subject. In these embodiments, the assay result is correlated to one or more such future changes. The following are preferred risk stratification embodiments.

In preferred risk stratification embodiments, these methods comprise determining a subject's risk for a future injury to renal function, and the assay result, for example a measured concentration of Beta-2-glycoprotein 1, is correlated to a likelihood of such a future injury to renal function. For example, the measured concentration may be compared to a threshold value, and an increased likelihood of suffering a future injury to renal function is assigned to the subject when the measured concentration is above the threshold, relative to a likelihood assigned when the measured concentration is below the threshold.

In other preferred risk stratification embodiments, these methods comprise determining a subject's risk for future reduced renal function, and the assay result, for example a measured concentration of Beta-2-glycoprotein 1, is correlated to a likelihood of such reduced renal function. For example, the measured concentration may be compared to a threshold value, and an increased likelihood of future reduced renal function is assigned to the subject when the measured concentration is above the threshold, relative to a likelihood assigned when the measured concentration is below the threshold.

In still other preferred risk stratification embodiments, these methods comprise determining a subject's likelihood for a future improvement in renal function, and the assay result, for example a measured concentration of Beta-2-glycoprotein 1, is correlated to a likelihood of such a future improvement in renal function. For example, the measured concentration may be compared to a threshold value, and an increased likelihood of a future improvement in renal function is assigned to the subject when the measured concentration is below the threshold, relative to a likelihood assigned when the measured concentration is above the threshold.

In yet other preferred risk stratification embodiments, these methods comprise determining a subject's risk for progression to ARF, and the assay result, for example a measured concentration of Beta-2-glycoprotein 1, is correlated to a likelihood of such progression to ARF. For example, the measured concentration may be compared to a threshold value, and an increased likelihood of progression to ARF is assigned to the subject when the measured concentration is above the threshold, relative to a likelihood assigned when the measured concentration is below the threshold.

And in other preferred risk stratification embodiments, these methods comprise determining a subject's outcome risk, and the assay result, for example a measured concentration of Beta-2-glycoprotein 1, is correlated to a likelihood of the occurrence of a clinical outcome related to a renal injury suffered by the subject. For example, the measured concentration may be compared to a threshold value, and an increased likelihood of one or more of: acute kidney injury, progression to a worsening stage of AKI, mortality, a requirement for renal replacement therapy, a requirement for withdrawal of renal toxins, end stage renal disease, heart failure, stroke, myocardial infarction, progression to chronic kidney disease, etc., is assigned to the subject when the measured concentration is above the threshold, relative to a likelihood assigned when the measured concentration is below the threshold.

In such risk stratification embodiments, preferably the likelihood or risk assigned is that an event of interest is more or less likely to occur within 180 days of the time at which the body fluid sample is obtained from the subject. In particularly preferred embodiments, the likelihood or risk assigned relates to an event of interest occurring within a shorter time period such as 18 months, 120 days, 90 days, 60 days, 45 days, 30 days, 21 days, 14 days, 7 days, 5 days, 96 hours, 72 hours, 48 hours, 36 hours, 24 hours, 12 hours, or less. A risk at 0 hours of the time at which the body fluid sample is obtained from the subject is equivalent to diagnosis of a current condition.

In preferred risk stratification embodiments, the subject is selected for risk stratification based on the pre-existence in the subject of one or more known risk factors for prerenal, intrinsic renal, or postrenal ARF. For example, a subject undergoing or having undergone major vascular surgery, coronary artery bypass, or other cardiac surgery; a subject having pre-existing congestive heart failure, preeclampsia, eclampsia, diabetes mellitus, hypertension, coronary artery disease, proteinuria, renal insufficiency, glomerular filtration below the normal range, cirrhosis, serum creatinine above the normal range, or sepsis; or a subject exposed to NSAIDs, cyclosporines, tacrolimus, aminoglycosides, foscarnet, ethylene glycol, hemoglobin, myoglobin, ifosfamide, heavy metals, methotrexate, radiopaque contrast agents, or streptozotocin are all preferred subjects for monitoring risks according to the methods described herein. This list is not meant to be limiting. By “pre-existence” in this context is meant that the risk factor exists at the time the body fluid sample is obtained from the subject. In particularly preferred embodiments, a subject is chosen for risk stratification based on an existing diagnosis of injury to renal function, reduced renal function, or ARF.

A variety of methods may be used by the skilled artisan to arrive at a desired threshold value for use in these methods. For example, the threshold value may be determined from a population of normal subjects by selecting a concentration representing the 75^(th), 85^(th), 90^(th), 95^(th), or 99^(th) percentile of Beta-2-glycoprotein 1 measured in such normal subjects. Alternatively, the threshold value may be determined from a population of subjects suffering from an injury to renal function or reduced renal function, but which do not progress to ARF (or some other clinical outcome such as death, dialysis, renal transplantation, etc.) by selecting a concentration representing the 75^(th), 85^(th), 90^(th), 95^(th), or 99^(th) percentile of Beta-2-glycoprotein 1 measured in such subjects. In another alternative, the threshold value may be determined from a prior measurement of Beta-2-glycoprotein 1 in the same subject; that is, a temporal change in the level of Beta-2-glycoprotein 1 in the subject may be used to assign risk to the subject. That is, an increasing concentration of Beta-2-glycoprotein 1 over time may be used to identify subjects at increased risk for future injury or progression of an existing renal injury; relative to a risk assigned when the concentration is stable or decreasing.

The ability of a particular test to distinguish two populations can be established using ROC analysis. For example, ROC curves established from a “first” subpopulation which is predisposed to one or more future changes in renal status, and a “second” subpopulation which is not so predisposed can be used to calculate a ROC curve, and the area under the curve provides a measure of the quality of the test. Preferably, the tests described herein provide a ROC curve area greater than 0.5, preferably at least 0.6, more preferably 0.7, still more preferably at least 0.8, even more preferably at least 0.9, and most preferably at least 0.95.

In certain aspects, the measured concentration of Beta-2-glycoprotein 1 is treated as a continuous variable. For example, any particular concentration can be converted into a probability of a future reduction in renal function for the subject. In yet another alternative, a threshold that can provide an acceptable level of specificity and sensitivity in separating a population of subjects into a “first” subpopulation which is predisposed to one or more future changes in renal status, and a “second” subpopulation which is not so predisposed. A threshold value is selected to separate this first and second population by one or more of the following measures of test accuracy:

-   an odds ratio greater than 1, preferably at least about 2 or more or     about 0.5 or less, more preferably at least about 3 or more or about     0.33 or less, still more preferably at least about 4 or more or     about 0.25 or less, even more preferably at least about 5 or more or     about 0.2 or less, and most preferably at least about 10 or more or     about 0.1 or less; -   a specificity of greater than 0.5, preferably at least about 0.6,     more preferably at least about 0.7, still more preferably at least     about 0.8, even more preferably at least about 0.9 and most     preferably at least about 0.95, with a corresponding sensitivity     greater than 0.2, preferably greater than about 0.3, more preferably     greater than about 0.4, still more preferably at least about 0.5,     even more preferably about 0.6, yet more preferably greater than     about 0.7, still more preferably greater than about 0.8, more     preferably greater than about 0.9, and most preferably greater than     about 0.95; -   a sensitivity of greater than 0.5, preferably at least about 0.6,     more preferably at least about 0.7, still more preferably at least     about 0.8, even more preferably at least about 0.9 and most     preferably at least about 0.95, with a corresponding specificity     greater than 0.2, preferably greater than about 0.3, more preferably     greater than about 0.4, still more preferably at least about 0.5,     even more preferably about 0.6, yet more preferably greater than     about 0.7, still more preferably greater than about 0.8, more     preferably greater than about 0.9, and most preferably greater than     about 0.95; -   at least about 75% sensitivity, combined with at least about 75%     specificity; -   a positive likelihood ratio (calculated as     sensitivity/(1−specificity)) of greater than 1, at least about 2,     more preferably at least about 3, still more preferably at least     about 5, and most preferably at least about 10; or -   a negative likelihood ratio (calculated as     (1-sensitivity)/specificity) of less than 1, less than or equal to     about 0.5, more preferably less than or equal to about 0.3, and most     preferably less than or equal to about 0.1. -   The term “about” in the context of any of the above measurements     refers to +/−5% of a given measurement.

Multiple thresholds may also be used to assess renal status in a subject. For example, a “first” subpopulation which is predisposed to one or more future changes in renal status, and a “second” subpopulation which is not so predisposed can be combined into a single group. This group is then subdivided into three or more equal parts (known as tertiles, quartiles, quintiles, etc., depending on the number of subdivisions). An odds ratio is assigned to subjects based on which subdivision they fall into. If one considers a tertile, the lowest or highest tertile can be used as a reference for comparison of the other subdivisions. This reference subdivision is assigned an odds ratio of 1. The second tertile is assigned an odds ratio that is relative to that first tertile. That is, someone in the second tertile might be 3 times more likely to suffer one or more future changes in renal status in comparison to someone in the first tertile. The third tertile is also assigned an odds ratio that is relative to that first tertile.

In certain embodiments, the assay method is an immunoassay. Antibodies for use in such assays will specifically bind the full length Beta-2-glycoprotein 1 protein, and may also bind one or more polypeptides that are “related” thereto, as that term is defined hereinafter. Numerous immunoassay formats are known to those of skill in the art. Preferred body fluid samples are selected from the group consisting of urine, blood, serum, saliva, tears, and plasma.

The foregoing method steps should not be interpreted to mean that the Beta-2-glycoprotein 1 assay result is used in isolation for risk stratification of a subject. Rather, additional variables or other clinical indicia may be included in the methods described herein. For example, a risk stratification method may combine the assay result with one or more variables measured for the subject selected from the group consisting of demographic information (e.g., weight, sex, age, race), medical history (e.g., family history, type of surgery, pre-existing disease such as aneurism, congestive heart failure, preeclampsia, eclampsia, diabetes mellitus, hypertension, coronary artery disease, proteinuria, renal insufficiency, or sepsis, type of toxin exposure such as NSAIDs, cyclosporines, tacrolimus, aminoglycosides, foscarnet, ethylene glycol, hemoglobin, myoglobin, ifosfamide, heavy metals, methotrexate, radiopaque contrast agents, or streptozotocin), clinical variables (e.g., blood pressure, temperature, respiration rate), risk scores (APACHE score, PREDICT score, TIMI Risk Score for UA/NSTEMI, Framingham Risk Score), a glomerular filtration rate, an estimated glomerular filtration rate, a urine production rate, a serum or plasma creatinine concentration, a urine creatinine concentration, a fractional excretion of sodium, a urine sodium concentration, a urine creatinine to serum or plasma creatinine ratio, a urine specific gravity, a urine osmolality, a urine urea nitrogen to plasma urea nitrogen ratio, a plasma BUN to creatinine ratio, a renal failure index calculated as urine sodium/(urine creatinine/plasma creatinine), a serum or plasma neutrophil gelatinase (NGAL) concentration, a urine NGAL concentration, a serum or plasma cystatin C concentration, a serum or plasma cardiac troponin concentration, a serum or plasma BNP concentration, a serum or plasma NTproBNP concentration, and a serum or plasma proBNP concentration. Other measures of renal function which may be combined with the Beta-2-glycoprotein 1 assay result are described hereinafter and in Harrison's Principles of Internal Medicine, 17^(th) Ed., McGraw Hill, New York, pages 1741-1830, and Current Medical Diagnosis & Treatment 2008, 47^(th) Ed, McGraw Hill, New York, pages 785-815, each of which are hereby incorporated by reference in their entirety.

Such additional variables may be measured in samples obtained at the same time as the sample used to determine the Beta-2-glycoprotein 1 assay result, or may be determined at an earlier or later time. The additional variables may also be measured on the same or different body fluid samples. For example, Beta-2-glycoprotein 1 may be measured in a serum or plasma sample and another biomarker may be measured in a urine sample. In addition, assignment of a likelihood may combine the Beta-2-glycoprotein 1 assay result with temporal changes in one or more such additional variables.

In other embodiments, the methods for evaluating renal status described herein are methods for diagnosing a renal injury in the subject; that is, assessing whether or not a subject has suffered from an injury to renal function, reduced renal function, or ARF. In these embodiments, the assay result is correlated to the occurrence or nonoccurrence of a change in renal status. The following are preferred diagnostic embodiments.

In preferred diagnostic embodiments, these methods comprise diagnosing the occurrence or nonoccurrence of an injury to renal function, and the assay result, for example a measured concentration of Beta-2-glycoprotein 1, is correlated to the occurrence or nonoccurrence of such an injury. For example, the measured concentration may be compared to a threshold value, and when the measured concentration is above the threshold, an increased likelihood of the occurrence of an injury to renal function is assigned to the subject relative to the likelihood assigned when the measured concentration is below the threshold; alternatively, when the measured concentration is below the threshold, a decreased likelihood of the nonoccurrence of an injury to renal function is assigned to the subject relative to the likelihood assigned when the measured concentration is above the threshold. As noted hereinafter, a “diagnosis” using the Beta-2-glycoprotein 1 assay result can take into consideration of other clinical indicia.

In other preferred diagnostic embodiments, these methods comprise diagnosing the occurrence or nonoccurrence of reduced renal function, and the assay result, for example a measured concentration of Beta-2-glycoprotein 1, is correlated to the occurrence or nonoccurrence of an injury causing reduced renal function. For example, the measured concentration may be compared to a threshold value, and when the measured concentration is above the threshold, an increased likelihood of the occurrence of an injury causing reduced renal function is assigned to the subject relative to the likelihood assigned when the measured concentration is below the threshold; alternatively, when the measured concentration is below the threshold, a decreased likelihood of the nonoccurrence of an injury causing reduced renal function is assigned to the subject relative to the likelihood assigned when the measured concentration is above the threshold.

In yet other preferred diagnostic embodiments, these methods comprise diagnosing the occurrence or nonoccurrence of ARF, and the assay result, for example a measured concentration of Beta-2-glycoprotein 1, is correlated to the occurrence or nonoccurrence of an injury causing ARF. For example, the measured concentration may be compared to a threshold value, and when the measured concentration is above the threshold, an increased likelihood of the occurrence of an injury causing ARF is assigned to the subject relative to the likelihood assigned when the measured concentration is below the threshold; alternatively, when the measured concentration is below the threshold, a decreased likelihood of the nonoccurrence of an injury causing ARF is assigned to the subject relative to the likelihood assigned when the measured concentration is above the threshold.

In still other preferred diagnostic embodiments, these methods comprise diagnosing a subject as being in need of renal replacement therapy, and the assay result, for example a measured concentration of Beta-2-glycoprotein 1, is correlated to a need for renal replacement therapy. For example, the measured concentration may be compared to a threshold value, and when the measured concentration is above the threshold, an increased likelihood of a present need for renal replacement therapy is assigned to the subject relative to the likelihood assigned when the measured concentration is below the threshold; alternatively, when the measured concentration is below the threshold, a decreased likelihood of a present need for renal replacement therapy is assigned to the subject relative to the likelihood assigned when the measured concentration is above the threshold.

In still other preferred diagnostic embodiments, these methods comprise diagnosing a subject as being in need of renal transplantation, and the assay result, for example a measured concentration of Beta-2-glycoprotein 1, is correlated to a need for renal transplantation. For example, the measured concentration may be compared to a threshold value, and when the measured concentration is above the threshold, an increased likelihood of a present need for renal transplantation is assigned to the subject relative to the likelihood assigned when the measured concentration is below the threshold; alternatively, when the measured concentration is below the threshold, a decreased likelihood of a present need for renal transplantation is assigned to the subject relative to the likelihood assigned when the measured concentration is above the threshold.

A variety of methods may be used by the skilled artisan to arrive at a desired threshold value. For example, the threshold value may be determined from a population of normal subjects by selecting a concentration representing the 75th, 85th, 90th, 95th, or 99th percentile of Beta-2-glycoprotein 1 measured in such normal subjects. In another alternative, the threshold value may be determined from a prior measurement of Beta-2-glycoprotein 1 in the same subject; that is, a temporal change in the level of Beta-2-glycoprotein 1 in the subject may be used to assign a diagnosis to the subject.

In yet another alternative, a threshold that can provide an acceptable level of specificity and sensitivity in separating a combined population of subjects into a “first” subpopulation having a disease of interest, and a “second” subpopulation not having a disease of interest. A threshold value is selected to separate this first and second population by one or more of the following measures of test accuracy:

-   an odds ratio greater than 1, preferably at least about 2 or more or     about 0.5 or less, more preferably at least about 3 or more or about     0.33 or less, still more preferably at least about 4 or more or     about 0.25 or less, even more preferably at least about 5 or more or     about 0.2 or less, and most preferably at least about 10 or more or     about 0.1 or less; -   a specificity of greater than 0.5, preferably at least about 0.6,     more preferably at least about 0.7, still more preferably at least     about 0.8, even more preferably at least about 0.9 and most     preferably at least about 0.95, with a corresponding sensitivity     greater than 0.2, preferably greater than about 0.3, more preferably     greater than about 0.4, still more preferably at least about 0.5,     even more preferably about 0.6, yet more preferably greater than     about 0.7, still more preferably greater than about 0.8, more     preferably greater than about 0.9, and most preferably greater than     about 0.95; -   a sensitivity of greater than 0.5, preferably at least about 0.6,     more preferably at least about 0.7, still more preferably at least     about 0.8, even more preferably at least about 0.9 and most     preferably at least about 0.95, with a corresponding specificity     greater than 0.2, preferably greater than about 0.3, more preferably     greater than about 0.4, still more preferably at least about 0.5,     even more preferably about 0.6, yet more preferably greater than     about 0.7, still more preferably greater than about 0.8, more     preferably greater than about 0.9, and most preferably greater than     about 0.95; -   at least about 75% sensitivity, combined with at least about 75%     specificity; -   a positive likelihood ratio (calculated as     sensitivity/(1-specificity)) of greater than 1, at least about 2,     more preferably at least about 3, still more preferably at least     about 5, and most preferably at least about 10; or -   a negative likelihood ratio (calculated as     (1−sensitivity)/specificity) of less than 1, less than or equal to     about 0.5, more preferably less than or equal to about 0.3, and most     preferably less than or equal to about 0.1. -   The term “about” in this context refers to +/−5% of a given     measurement.

Multiple thresholds may also be used to assess renal status in a subject. For example, a “first” subpopulation of individuals having a condition of interest, and a “second” subpopulation which does not can be combined into a single group. This group is then subdivided into three or more equal parts (known as tertiles, quartiles, quintiles, etc., depending on the number of subdivisions). An odds ratio is assigned to subjects based on which subdivision they fall into. If one considers a tertile, the lowest or highest tertile can be used as a reference for comparison of the other subdivisions. This reference subdivision is assigned an odds ratio of 1. The second tertile is assigned an odds ratio that is relative to that first tertile. That is, someone in the second tertile might be 3 times more likely to have the condition in comparison to someone in the first tertile. The third tertile is also assigned an odds ratio that is relative to that first tertile.

In certain embodiments, the assay method is an immunoassay. Antibodies for use in such assays will specifically bind the full length Beta-2-glycoprotein 1 protein, and may also bind one or more polypeptides that are “related” thereto, as that term is defined hereinafter. Numerous immunoassay formats are known to those of skill in the art. Preferred body fluid samples are selected from the group consisting of urine, blood, serum, and plasma.

The foregoing method steps should not be interpreted to mean that the Beta-2-glycoprotein 1 assay result is used in isolation for diagnosis of a subject. Rather, additional variables may be included in the methods described herein. For example, a diagnosis may combine the assay result with one or more variables measured for the subject selected from the group consisting of demographic information (e.g., weight, sex, age, race), medical history (e.g., family history, type of surgery, pre-existing disease such as aneurism, congestive heart failure, preeclampsia, eclampsia, diabetes mellitus, hypertension, coronary artery disease, proteinuria, renal insufficiency, or sepsis, type of toxin exposure such as NSAIDs, cyclosporines, tacrolimus, aminoglycosides, foscarnet, ethylene glycol, hemoglobin, myoglobin, ifosfamide, heavy metals, methotrexate, radiopaque contrast agents, or streptozotocin), clinical variables (e.g., blood pressure, temperature, respiration rate), risk scores (APACHE score, PREDICT score, TIMI Risk Score for UA/NSTEMI, Framingham Risk Score), a glomerular filtration rate, an estimated glomerular filtration rate, a urine production rate, a serum or plasma creatinine concentration, a urine creatinine concentration, a fractional excretion of sodium, a urine sodium concentration, a urine creatinine to serum or plasma creatinine ratio, a urine specific gravity, a urine osmolality, a urine urea nitrogen to plasma urea nitrogen ratio, a plasma BUN to creatinine ratio, a renal failure index calculated as urine sodium/(urine creatinine/plasma creatinine), a serum or plasma neutrophil gelatinase (NGAL) concentration, a urine NGAL concentration, a serum or plasma cystatin C concentration, a serum or plasma BNP concentration, a serum or plasma NTproBNP concentration, and a serum or plasma proBNP concentration. Other measures of renal function which may be combined with the Beta-2-glycoprotein 1 assay result are described hereinafter and in Harrison's Principles of Internal Medicine, 17^(th) Ed., McGraw Hill, New York, pages 1741-1830, and Current Medical Diagnosis & Treatment 2008, 47^(th) Ed, McGraw Hill, New York, pages 785-815, each of which are hereby incorporated by reference in their entirety.

Such additional variables may be measured in samples obtained at the same time as the sample used to determine the Beta-2-glycoprotein 1 assay result, or may be determined at an earlier or later time. The additional variables may also be measured on the same or different body fluid samples. For example, Beta-2-glycoprotein 1 may be measured in a serum or plasma sample and another biomarker may be measured in a urine sample. In addition, a diagnostic method may combine the Beta-2-glycoprotein 1 assay result with temporal changes in one or more such additional variables.

In still other embodiments, the methods for evaluating renal status described herein are methods for monitoring a renal injury in the subject; that is, assessing whether or not renal function is improving or worsening in a subject who has suffered from an injury to renal function, reduced renal function, or ARF. In these embodiments, the assay result is correlated to the occurrence or nonoccurrence of a change in renal status. The following are preferred monitoring embodiments.

In preferred monitoring embodiments, these methods comprise monitoring renal status in a subject suffering from an injury to renal function, and the assay result, for example a measured concentration of Beta-2-glycoprotein 1, is correlated to the occurrence or nonoccurrence of a change in renal status in the subject. For example, the measured concentration may be compared to a threshold value, and when the measured concentration is above the threshold, a worsening of renal function may be assigned to the subject; alternatively, when the measured concentration is below the threshold, an improvement of renal function may be assigned to the subject.

In other preferred monitoring embodiments, these methods comprise monitoring renal status in a subject suffering from reduced renal function, and the assay result, for example a measured concentration of Beta-2-glycoprotein 1, is correlated to the occurrence or nonoccurrence of a change in renal status in the subject. For example, the measured concentration may be compared to a threshold value, and when the measured concentration is above the threshold, a worsening of renal function may be assigned to the subject; alternatively, when the measured concentration is below the threshold, an improvement of renal function may be assigned to the subject.

In yet other preferred monitoring embodiments, these methods comprise monitoring renal status in a subject suffering from acute renal failure, and the assay result, for example a measured concentration of Beta-2-glycoprotein 1, is correlated to the occurrence or nonoccurrence of a change in renal status in the subject. For example, the measured concentration may be compared to a threshold value, and when the measured concentration is above the threshold, a worsening of renal function may be assigned to the subject; alternatively, when the measured concentration is below the threshold, an improvement of renal function may be assigned to the subject.

In other additional preferred monitoring embodiments, these methods comprise monitoring renal status in a subject at risk of an injury to renal function due to the pre-existence of one or more known risk factors for prerenal, intrinsic renal, or postrenal ARF, and the assay result, for example a measured concentration of Beta-2-glycoprotein 1, is correlated to the occurrence or nonoccurrence of a change in renal status in the subject. For example, the measured concentration may be compared to a threshold value, and when the measured concentration is above the threshold, a worsening of renal function may be assigned to the subject; alternatively, when the measured concentration is below the threshold, an improvement of renal function may be assigned to the subject.

A variety of methods may be used by the skilled artisan to arrive at a desired threshold value. For example, the threshold value may be determined from a population of normal subjects by selecting a concentration representing the 75th, 85th, 90th, 95th, or 99th percentile of Beta-2-glycoprotein 1 measured in such normal subjects. In another alternative, the threshold value may be determined from a prior measurement of Beta-2-glycoprotein 1 in the same subject; that is, a temporal change in the level of Beta-2-glycoprotein 1 in the subject may be used to assign a diagnosis to the subject.

In yet another alternative, a threshold that can provide an acceptable level of specificity and sensitivity in separating a combined population of subjects into a “first” subpopulation having a disease of interest and whose renal function worsens, and a “second” subpopulation having a disease of interest and whose renal function improves. A threshold value is selected to separate this first and second population by one or more of the following measures of test accuracy:

-   an odds ratio greater than 1, preferably at least about 2 or more or     about 0.5 or less, more preferably at least about 3 or more or about     0.33 or less, still more preferably at least about 4 or more or     about 0.25 or less, even more preferably at least about 5 or more or     about 0.2 or less, and most preferably at least about 10 or more or     about 0.1 or less; -   a specificity of greater than 0.5, preferably at least about 0.6,     more preferably at least about 0.7, still more preferably at least     about 0.8, even more preferably at least about 0.9 and most     preferably at least about 0.95, with a corresponding sensitivity     greater than 0.2, preferably greater than about 0.3, more preferably     greater than about 0.4, still more preferably at least about 0.5,     even more preferably about 0.6, yet more preferably greater than     about 0.7, still more preferably greater than about 0.8, more     preferably greater than about 0.9, and most preferably greater than     about 0.95; -   a sensitivity of greater than 0.5, preferably at least about 0.6,     more preferably at least about 0.7, still more preferably at least     about 0.8, even more preferably at least about 0.9 and most     preferably at least about 0.95, with a corresponding specificity     greater than 0.2, preferably greater than about 0.3, more preferably     greater than about 0.4, still more preferably at least about 0.5,     even more preferably about 0.6, yet more preferably greater than     about 0.7, still more preferably greater than about 0.8, more     preferably greater than about 0.9, and most preferably greater than     about 0.95; -   at least about 75% sensitivity, combined with at least about 75%     specificity; -   a positive likelihood ratio (calculated as     sensitivity/(1−specificity)) of greater than 1, at least about 2,     more preferably at least about 3, still more preferably at least     about 5, and most preferably at least about 10; or -   a negative likelihood ratio (calculated as     (1−sensitivity)/specificity) of less than 1, less than or equal to     about 0.5, more preferably less than or equal to about 0.3, and most     preferably less than or equal to about 0.1. -   The term “about” in this context refers to +/−5% of a given     measurement.

Multiple thresholds may also be used to monitor renal status in a subject. For example, a “first” subpopulation of individuals in which renal function is improving (or worsening), and a “second” subpopulation of individuals which do not can be combined into a single group. This group is then subdivided into three or more equal parts (known as tertiles, quartiles, quintiles, etc., depending on the number of subdivisions). An odds ratio is assigned to subjects based on which subdivision they fall into. If one considers a tertile, the lowest or highest tertile can be used as a reference for comparison of the other subdivisions. This reference subdivision is assigned an odds ratio of 1. The second tertile is assigned an odds ratio that is relative to that first tertile. That is, someone in the second tertile might be 3 times more likely to improve (or worsen) in comparison to someone in the first tertile. The third tertile is also assigned an odds ratio that is relative to that first tertile.

In certain embodiments, the assay method is an immunoassay. Antibodies for use in such assays will specifically bind the full length Beta-2-glycoprotein 1 protein, and may also bind one or more polypeptides that are “related” thereto, as that term is defined hereinafter. Numerous immunoassay formats are known to those of skill in the art. Preferred body fluid samples are selected from the group consisting of urine, blood, serum, saliva, tears, and plasma.

The foregoing method steps should not be interpreted to mean that the Beta-2-glycoprotein 1 assay result is used in isolation for monitoring a subject. Rather, additional variables may be included in the methods described herein. For example, a monitoring may combine the assay result with one or more variables measured for the subject selected from the group consisting of demographic information (e.g., weight, sex, age, race), medical history (e.g., family history, type of surgery, pre-existing disease such as aneurism, congestive heart failure, preeclampsia, eclampsia, diabetes mellitus, hypertension, coronary artery disease, proteinuria, renal insufficiency, or sepsis, type of toxin exposure such as NSAIDs, cyclosporines, tacrolimus, aminoglycosides, foscarnet, ethylene glycol, hemoglobin, myoglobin, ifosfamide, heavy metals, methotrexate, radiopaque contrast agents, or streptozotocin), clinical variables (e.g., blood pressure, temperature, respiration rate), risk scores (APACHE score, PREDICT score, TIMI Risk Score for UA/NSTEMI, Framingham Risk Score), a glomerular filtration rate, an estimated glomerular filtration rate, a urine production rate, a serum or plasma creatinine concentration, a urine creatinine concentration, a fractional excretion of sodium, a urine sodium concentration, a urine creatinine to serum or plasma creatinine ratio, a urine specific gravity, a urine osmolality, a urine urea nitrogen to plasma urea nitrogen ratio, a plasma BUN to creatinine ratio, a renal failure index calculated as urine sodium/(urine creatinine/plasma creatinine), a serum or plasma neutrophil gelatinase (NGAL) concentration, a urine NGAL concentration, a serum or plasma cystatin C concentration, a serum or plasma BNP concentration, a serum or plasma NTproBNP concentration, and a serum or plasma proBNP concentration. Other measures of renal function which may be combined with the Beta-2-glycoprotein 1 assay result are described hereinafter and in Harrison's Principles of Internal Medicine, 17^(th) Ed., McGraw Hill, New York, pages 1741-1830, and Current Medical Diagnosis & Treatment 2008, 47^(th) Ed, McGraw Hill, New York, pages 785-815, each of which are hereby incorporated by reference in their entirety.

Such additional variables may be measured in samples obtained at the same time as the sample used to determine the Beta-2-glycoprotein 1 assay result, or may be determined at an earlier or later time. The additional variables may also be measured on the same or different body fluid samples. For example, Beta-2-glycoprotein 1 may be measured in a serum or plasma sample and another biomarker may be measured in a urine sample. In addition, a monitoring method may combine the Beta-2-glycoprotein 1 assay result with temporal changes in one or more such additional variables.

In still other embodiments, the methods for evaluating renal status described herein are methods for classifying a renal injury in the subject; that is, determining whether a renal injury in a subject is prerenal, intrinsic renal, or postrenal; and/or further subdividing these classes into subclasses such as acute tubular injury, acute glomerulonephritis acute tubulointerstitial nephritis, acute vascular nephropathy, or infiltrative disease. In these embodiments, the assay result is correlated to a particular class and/or subclass. The following are preferred classification embodiments.

In preferred classification embodiments, these methods comprise determining whether a renal injury in a subject is prerenal, intrinsic renal, or postrenal; and/or further subdividing these classes into subclasses such as acute tubular injury, acute glomerulonephritis acute tubulointerstitial nephritis, acute vascular nephropathy, or infiltrative disease, and the assay result, for example a measured concentration of Beta-2-glycoprotein 1, is correlated to the injury classification for the subject. For example, the measured concentration may be compared to a threshold value, and when the measured concentration is above the threshold, a particular classification is assigned; alternatively, when the measured concentration is below the threshold, a different classification may be assigned to the subject.

A variety of methods may be used by the skilled artisan to arrive at a desired threshold value. For example, the threshold value may be determined from a population of subjects not having a particular classification (e.g., a “control” group) by selecting a concentration representing the 75th, 85th, 90th, 95th, or 99th percentile of Beta-2-glycoprotein 1 measured in such control subjects. In another alternative, the threshold value may be determined from a prior measurement of Beta-2-glycoprotein 1 in the same subject; that is, a temporal change in the level of Beta-2-glycoprotein 1 in the subject may be used to assign a classification to the subject.

In yet another alternative, a threshold that can provide an acceptable level of specificity and sensitivity in separating a combined population of subjects into a “first” subpopulation having a particular classification, and a “second” subpopulation having a different classification. A threshold value is selected to separate this first and second population by one or more of the following measures of test accuracy:

-   an odds ratio greater than 1, preferably at least about 2 or more or     about 0.5 or less, more preferably at least about 3 or more or about     0.33 or less, still more preferably at least about 4 or more or     about 0.25 or less, even more preferably at least about 5 or more or     about 0.2 or less, and most preferably at least about 10 or more or     about 0.1 or less; -   a specificity of greater than 0.5, preferably at least about 0.6,     more preferably at least about 0.7, still more preferably at least     about 0.8, even more preferably at least about 0.9 and most     preferably at least about 0.95, with a corresponding sensitivity     greater than 0.2, preferably greater than about 0.3, more preferably     greater than about 0.4, still more preferably at least about 0.5,     even more preferably about 0.6, yet more preferably greater than     about 0.7, still more preferably greater than about 0.8, more     preferably greater than about 0.9, and most preferably greater than     about 0.95; -   a sensitivity of greater than 0.5, preferably at least about 0.6,     more preferably at least about 0.7, still more preferably at least     about 0.8, even more preferably at least about 0.9 and most     preferably at least about 0.95, with a corresponding specificity     greater than 0.2, preferably greater than about 0.3, more preferably     greater than about 0.4, still more preferably at least about 0.5,     even more preferably about 0.6, yet more preferably greater than     about 0.7, still more preferably greater than about 0.8, more     preferably greater than about 0.9, and most preferably greater than     about 0.95; -   at least about 75% sensitivity, combined with at least about 75%     specificity; -   a positive likelihood ratio (calculated as     sensitivity/(1−specificity)) of greater than 1, at least about 2,     more preferably at least about 3, still more preferably at least     about 5, and most preferably at least about 10; or -   a negative likelihood ratio (calculated as     (1−sensitivity)/specificity) of less than 1, less than or equal to     about 0.5, more preferably less than or equal to about 0.3, and most     preferably less than or equal to about 0.1. -   The term “about” in this context refers to +/−5% of a given     measurement.

Multiple thresholds may also be used to classify a renal injury in a subject. For example, a “first” subpopulation of individuals having a particular classification, and a “second” subpopulation having a different classification, can be combined into a single group. This group is then subdivided into three or more equal parts (known as tertiles, quartiles, quintiles, etc., depending on the number of subdivisions). An odds ratio is assigned to subjects based on which subdivision they fall into. If one considers a tertile, the lowest or highest tertile can be used as a reference for comparison of the other subdivisions. This reference subdivision is assigned an odds ratio of 1. The second tertile is assigned an odds ratio that is relative to that first tertile. That is, someone in the second tertile might be 3 times more likely to have a particular classification in comparison to someone in the first tertile. The third tertile is also assigned an odds ratio that is relative to that first tertile.

In certain embodiments, the assay method is an immunoassay. Antibodies for use in such assays will specifically bind the full length Beta-2-glycoprotein 1 protein, and may also bind one or more polypeptides that are “related” thereto, as that term is defined hereinafter. Numerous immunoassay formats are known to those of skill in the art. Preferred body fluid samples are selected from the group consisting of urine, blood, serum, and plasma.

The foregoing method steps should not be interpreted to mean that the Beta-2-glycoprotein 1 assay result is used in isolation for classification of an injury in a subject. Rather, additional variables may be included in the methods described herein. For example, a classification may combine the assay result with one or more variables measured for the subject selected from the group consisting of demographic information (e.g., weight, sex, age, race), medical history (e.g., family history, type of surgery, pre-existing disease such as aneurism, congestive heart failure, preeclampsia, eclampsia, diabetes mellitus, hypertension, coronary artery disease, proteinuria, renal insufficiency, or sepsis, type of toxin exposure such as NSAIDs, cyclosporines, tacrolimus, aminoglycosides, foscarnet, ethylene glycol, hemoglobin, myoglobin, ifosfamide, heavy metals, methotrexate, radiopaque contrast agents, or streptozotocin), clinical variables (e.g., blood pressure, temperature, respiration rate), risk scores (APACHE score, PREDICT score, TIMI Risk Score for UA/NSTEMI, Framingham Risk Score, Thaker score to predict acute renal failure after cardiac surgery, etc.), a glomerular filtration rate, an estimated glomerular filtration rate, a urine production rate, a serum or plasma creatinine concentration, a urine creatinine concentration, a fractional excretion of sodium, a urine sodium concentration, a urine creatinine to serum or plasma creatinine ratio, a urine specific gravity, a urine osmolality, a urine urea nitrogen to plasma urea nitrogen ratio, a plasma BUN to creatinine ratio, a renal failure index calculated as urine sodium/(urine creatinine/plasma creatinine), a serum or plasma neutrophil gelatinase (NGAL) concentration, a urine NGAL concentration, a serum or plasma cystatin C concentration, a serum or plasma BNP concentration, a serum or plasma NTproBNP concentration, and a serum or plasma proBNP concentration. Other measures of renal function which may be combined with the Beta-2-glycoprotein 1 assay result are described hereinafter and in Harrison's Principles of Internal Medicine, 17^(th) Ed., McGraw Hill, New York, pages 1741-1830, and Current Medical Diagnosis & Treatment 2008, 47^(th) Ed, McGraw Hill, New York, pages 785-815, each of which are hereby incorporated by reference in their entirety.

Such additional variables may be measured in samples obtained at the same time as the sample used to determine the Beta-2-glycoprotein 1 assay result, or may be determined at an earlier or later time. The additional variables may also be measured on the same or different body fluid samples. For example, Beta-2-glycoprotein 1 may be measured in a serum or plasma sample and another biomarker may be measured in a urine sample. In addition, a monitoring method may combine the Beta-2-glycoprotein 1 assay result with temporal changes in one or more such additional variables.

In various related aspects, the present invention also relates to devices and kits for performing the methods described herein. Suitable kits comprise reagents sufficient for performing at least one of the described Beta-2-glycoprotein 1 assays, together with instructions for performing the described threshold comparisons.

In certain embodiments, reagents for performing such assays are provided in an assay device, and such assay devices may be included in such a kit. Preferred reagents can comprise one or more solid phase antibodies, the solid phase antibody comprising antibody that detects the intended biomarker target(s) bound to a solid support. In the case of sandwich immunoassays, such reagents can also include one or more detectably labeled antibodies, the detectably labeled antibody comprising antibody that detects the intended biomarker target(s) bound to a detectable label. Additional optional elements that may be provided as part of an assay device are described hereinafter.

Detectable labels may include molecules that are themselves detectable (e.g., fluorescent moieties, electrochemical labels, ecl (electrochemical luminescence) labels, metal chelates, colloidal metal particles, etc.) as well as molecules that may be indirectly detected by production of a detectable reaction product (e.g., enzymes such as horseradish peroxidase, alkaline phosphatase, etc.) or through the use of a specific binding molecule which itself may be detectable (e.g., a labeled antibody that binds to the second antibody, biotin, digoxigenin, maltose, oligohistidine, 2,4-dintrobenzene, phenylarsenate, ssDNA, dsDNA, etc.).

Generation of a signal from the signal development element can be performed using various optical, acoustical, and electrochemical methods well known in the art. Examples of detection modes include fluorescence, radiochemical detection, reflectance, absorbance, amperometry, conductance, impedance, interferometry, ellipsometry, etc. In certain of these methods, the solid phase antibody is coupled to a transducer (e.g., a diffraction grating, electrochemical sensor, etc) for generation of a signal, while in others, a signal is generated by a transducer that is spatially separate from the solid phase antibody (e.g., a fluorometer that employs an excitation light source and an optical detector). This list is not meant to be limiting. Antibody-based biosensors may also be employed to determine the presence or amount of analytes that optionally eliminate the need for a labeled molecule.

DETAILED DESCRIPTION OF THE INVENTION

The present invention relates to methods and compositions for diagnosis, differential diagnosis, risk stratification, monitoring, classifying and determination of treatment regimens in subjects suffering or at risk of suffering from injury to renal function, reduced renal function and/or acute renal failure through measurement of Beta-2-glycoprotein 1.

For purposes of this document, the following definitions apply:

-   As used herein, an “injury to renal function” is an abrupt (within     14 days, preferably within 7 days, more preferably within 72 hours,     and still more preferably within 48 hours) measurable reduction in a     measure of renal function. Such an injury may be identified, for     example, by a decrease in glomerular filtration rate or estimated     GFR, a reduction in urine output, an increase in serum creatinine,     an increase in serum cystatin C, a requirement for renal replacement     therapy, etc. “Improvement in Renal Function” is an abrupt (within     14 days, preferably within 7 days, more preferably within 72 hours,     and still more preferably within 48 hours) measurable increase in a     measure of renal function. Preferred methods for measuring and/or     estimating GFR are described hereinafter. -   As used herein, “reduced renal function” is an abrupt (within 14     days, preferably within 7 days, more preferably within 72 hours, and     still more preferably within 48 hours) reduction in kidney function     identified by an absolute increase in serum creatinine of greater     than or equal to 0.1 mg/dL (≧8.8 μmol/L), a percentage increase in     serum creatinine of greater than or equal to 20% (1.2-fold from     baseline), or a reduction in urine output (documented oliguria of     less than 0.5 ml/kg per hour). -   As used herein, “acute renal failure” or “ARF” is an abrupt (within     14 days, preferably within 7 days, more preferably within 72 hours,     and still more preferably within 48 hours) reduction in kidney     function identified by an absolute increase in serum creatinine of     greater than or equal to 0.3 mg/dl (≧26.4 μmol/l), a percentage     increase in serum creatinine of greater than or equal to 50%     (1.5-fold from baseline), or a reduction in urine output (documented     oliguria of less than 0.5 ml/kg per hour for at least 6 hours). This     term is synonymous with “acute kidney injury” or “AKI.”

As used herein, the term “Beta-2-glycoprotein 1” refers to one or polypeptides present in a biological sample that are derived from the Beta-2-glycoprotein 1 precursor (Swiss-Prot P02749 (SEQ ID NO: 1)).

        10         20         30         40 MISPVLILFS SFLCHVAIAG RTCPKPDDLP FSTVVPLKTF         50         60         70         80 YEPGEEITYS CKPGYVSRGG MRKFICPLTG LWPINTLKCT         90        100        110        120 PRVCPFAGIL ENGAVRYTTF EYPNTISFSC NTGFYLNGAD        130        140        150        160 SAKCTEEGKW SPELPVCAPI ICPPPSIPTF ATLRVYKPSA        170        180        190        200 GNNSLYRDTA VFECLPQHAM FGNDTITCTT HGNWTKLPEC        210        220        230        240 REVKCPFPSR PDNGFVNYPA KPTLYYKDKA TFGCHDGYSL        250        260        270        280 DGPEEIECTK LGNWSAMPSC KASCKVPVKK ATVVYQGERV        290        300        310        320 KIQEKFKNGM LHGDKVSFFC KNKEKKCSYT EDAQCIDGTI        330        340 EVPKCFKEHS SLAFWKTDAS DVKPC

The following domains have been identified in Beta-2-glycoprotein 1:

Residues Length Domain ID 1-19 19 Signal sequence 20-345 326 Beta-2-glycoprotein 1

In addition, several naturally occurring variants have been identified:

Residue Change 5 V to A 107 S to N 154 R to H 266 V to L 325 C to G 335 W to S

In this regard, the skilled artisan will understand that the signals obtained from an immunoassay are a direct result of complexes formed between one or more antibodies and the target biomolecule (i.e., the analyte) and polypeptides containing the necessary epitope(s) to which the antibodies bind. While such assays may detect the full length Beta-2-glycoprotein 1 molecule and the assay result be expressed as a concentration of Beta-2-glycoprotein 1, the signal from the assay is actually a result of all such “immunoreactive” polypeptides present in the sample. Expression of Beta-2-glycoprotein 1 may also be determined by means other than immunoassays, including protein measurements (such as dot blots, western blots, chromatographic methods, mass spectrometry, etc.) and nucleic acid measurements (mRNA quatitation). This list is not meant to be limiting.

As used herein, the term “relating a signal to the presence or amount” of an analyte reflects this understanding. Assay signals are typically related to the presence or amount of an analyte through the use of a standard curve calculated using known concentrations of the analyte of interest. As the term is used herein, an assay is “configured to detect” an analyte if an assay can generate a detectable signal indicative of the presence or amount of a physiologically relevant concentration of the analyte. Because an antibody epitope is on the order of 8 amino acids, an immunoassay configured to detect Beta-2-glycoprotein 1 will also detect polypeptides related to the Beta-2-glycoprotein 1 sequence, so long as those polypeptides contain the epitope(s) necessary to bind to the antibody or antibodies used in the assay. The term “related marker” as used herein with regard to a biomarker such as Beta-2-glycoprotein 1 refers to one or more fragments of a particular marker or its biosynthetic parent that may be detected as a surrogate for the marker itself or as independent biomarkers. The term also refers to one or more polypeptides present in a biological sample that are derived from the Beta-2-glycoprotein 1 precursor complexed to additional species, such as binding proteins, receptors, heparin, lipids, sugars, etc.

The term “subject” as used herein refers to a human or non-human organism. Thus, the methods and compositions described herein are applicable to both human and veterinary disease. Further, while a subject is preferably a living organism, the invention described herein may be used in post-mortem analysis as well. Preferred subjects are humans, and most preferably “patients,” which as used herein refers to living humans that are receiving medical care for a disease or condition. This includes persons with no defined illness who are being investigated for signs of pathology.

Preferably, an analyte is measured in a sample. Such a sample may be obtained from a subject, or may be obtained from biological materials intended to be provided to the subject. For example, a sample may be obtained from a kidney being evaluated for possible transplantation into a subject, and an analyte measurement used to evaluate the kidney for preexisting damage. Preferred samples are body fluid samples.

The term “body fluid sample” as used herein refers to a sample of bodily fluid obtained for the purpose of diagnosis, prognosis, classification or evaluation of a subject of interest, such as a patient or transplant donor. In certain embodiments, such a sample may be obtained for the purpose of determining the outcome of an ongoing condition or the effect of a treatment regimen on a condition. Preferred body fluid samples include blood, serum, plasma, cerebrospinal fluid, urine, saliva, sputum, and pleural effusions. In addition, one of skill in the art would realize that certain body fluid samples would be more readily analyzed following a fractionation or purification procedure, for example, separation of whole blood into serum or plasma components.

The term “diagnosis” as used herein refers to methods by which the skilled artisan can estimate and/or determine the probability (“a likelihood”) of whether or not a patient is suffering from a given disease or condition. In the case of the present invention, “diagnosis” includes using the results of a Beta-2-glycoprotein 1 assay of the present invention, optionally together with other clinical characteristics, to arrive at a diagnosis (that is, the occurrence or nonoccurrence) of an acute renal injury or ARF for the subject from which a sample was obtained and assayed. That such a diagnosis is “determined” is not meant to imply that the diagnosis is 100% accurate. Many biomarkers are indicative of multiple conditions. The skilled clinician does not use biomarker results in an informational vacuum, but rather test results are used together with other clinical indicia to arrive at a diagnosis. Thus, a measured biomarker level on one side of a predetermined diagnostic threshold indicates a greater likelihood of the occurrence of disease in the subject relative to a measured level on the other side of the predetermined diagnostic threshold.

Similarly, a prognostic risk signals a probability (“a likelihood”) that a given course or outcome will occur. A level or a change in level of a prognostic indicator, which in turn is associated with an increased probability of morbidity (e.g., worsening renal function, future ARF, or death) is referred to as being “indicative of an increased likelihood” of an adverse outcome in a patient.

Beta-2-Glycoprotein 1 Assays

In general, immunoassays involve contacting a sample containing or suspected of containing a biomarker of interest with at least one antibody that specifically binds to the biomarker. A signal is then generated indicative of the presence or amount of complexes formed by the binding of polypeptides in the sample to the antibody. The signal is then related to the presence or amount of the biomarker in the sample. Numerous methods and devices are well known to the skilled artisan for the detection and analysis of biomarkers. See, e.g., U.S. Pat. Nos. 6,143,576; 6,113,855; 6,019,944; 5,985,579; 5,947,124; 5,939,272; 5,922,615; 5,885,527; 5,851,776; 5,824,799; 5,679,526; 5,525,524; and 5,480,792, and The Immunoassay Handbook, David Wild, ed. Stockton Press, New York, 1994, each of which is hereby incorporated by reference in its entirety, including all tables, figures and claims.

The assay devices and methods known in the art can utilize labeled molecules in various sandwich, competitive, or non-competitive assay formats, to generate a signal that is related to the presence or amount of the biomarker of interest. Suitable assay formats also include chromatographic, mass spectrographic, and protein “blotting” methods. Additionally, certain methods and devices, such as biosensors and optical immunoassays, may be employed to determine the presence or amount of analytes without the need for a labeled molecule. See, e.g., U.S. Pat. Nos. 5,631,171; and 5,955,377, each of which is hereby incorporated by reference in its entirety, including all tables, figures and claims. One skilled in the art also recognizes that robotic instrumentation including but not limited to Beckman ACCESS®, Abbott AXSYM®, Roche ELECSYS®, Dade Behring STRATUS® systems are among the immunoassay analyzers that are capable of performing immunoassays. But any suitable immunoassay may be utilized, for example, enzyme-linked immunoassays (ELISA), radioimmunoassays (RIAs), competitive binding assays, and the like.

Antibodies or other polypeptides may be immobilized onto a variety of solid supports for use in assays. Solid phases that may be used to immobilize specific binding members include include those developed and/or used as solid phases in solid phase binding assays. Examples of suitable solid phases include membrane filters, cellulose-based papers, beads (including polymeric, latex and paramagnetic particles), glass, silicon wafers, microparticles, nanoparticles, TentaGels, AgroGels, PEGA gels, SPOCC gels, and multiple-well plates. An assay strip could be prepared by coating the antibody or a plurality of antibodies in an array on solid support. This strip could then be dipped into the test sample and then processed quickly through washes and detection steps to generate a measurable signal, such as a colored spot. Antibodies or other polypeptides may be bound to specific zones of assay devices either by conjugating directly to an assay device surface, or by indirect binding. In an example of the later case, antibodies or other polypeptides may be immobilized on particles or other solid supports, and that solid support immobilized to the device surface.

Biological assays require methods for detection, and one of the most common methods for quantitation of results is to conjugate a detectable label to a protein or nucleic acid that has affinity for one of the components in the biological system being studied. Detectable labels may include molecules that are themselves detectable (e.g., fluorescent moieties, electrochemical labels, metal chelates, etc.) as well as molecules that may be indirectly detected by production of a detectable reaction product (e.g., enzymes such as horseradish peroxidase, alkaline phosphatase, etc.) or by a specific binding molecule which itself may be detectable (e.g., biotin, digoxigenin, maltose, oligohistidine, 2,4-dintrobenzene, phenylarsenate, ssDNA, dsDNA, etc.).

Preparation of solid phases and detectable label conjugates often comprise the use of chemical cross-linkers. Cross-linking reagents contain at least two reactive groups, and are divided generally into homofunctional cross-linkers (containing identical reactive groups) and heterofunctional cross-linkers (containing non-identical reactive groups). Homobifunctional cross-linkers that couple through amines, sulfhydryls or react non-specifically are available from many commercial sources. Maleimides, alkyl and aryl halides, alpha-haloacyls and pyridyl disulfides are thiol reactive groups. Maleimides, alkyl and aryl halides, and alpha-haloacyls react with sulfhydryls to form thiol ether bonds, while pyridyl disulfides react with sulfhydryls to produce mixed disulfides. The pyridyl disulfide product is cleavable. Imidoesters are also very useful for protein-protein cross-links. A variety of heterobifunctional cross-linkers, each combining different attributes for successful conjugation, are commercially available.

In certain aspects, the present invention provides kits for the analysis of Beta-2-glycoprotein 1, and optionally one or more other markers. The kit comprises reagents for the analysis of at least one test sample which comprise at least one antibody that binds Beta-2-glycoprotein 1. The kit can also include devices and instructions for performing one or more of the diagnostic and/or prognostic correlations described herein. Preferred kits will comprise an antibody pair for performing a sandwich assay, or a labeled species for performing a competitive assay, for the analyte. Preferably, an antibody pair comprises a first antibody conjugated to a solid phase and a second antibody conjugated to a detectable label, wherein each of the first and second antibodies that bind Beta-2-glycoprotein 1. Most preferably each of the antibodies are monoclonal antibodies. The instructions for use of the kit and performing the correlations can be in the form of labeling, which refers to any written or recorded material that is attached to, or otherwise accompanies a kit at any time during its manufacture, transport, sale or use. For example, the term labeling encompasses advertising leaflets and brochures, packaging materials, instructions, audio or video cassettes, computer discs, as well as writing imprinted directly on kits.

Beta-2-Glycoprotein 1 Antibodies

The term “antibody” as used herein refers to a peptide or polypeptide derived from, modeled after or substantially encoded by an immunoglobulin gene or immunoglobulin genes, or fragments thereof, capable of specifically binding an antigen or epitope. See, e.g. Fundamental Immunology, 3rd Edition, W. E. Paul, ed., Raven Press, N.Y. (1993); Wilson (1994; J. Immunol. Methods 175:267-273; Yarmush (1992) J. Biochem. Biophys. Methods 25:85-97. The term antibody includes antigen-binding portions, i.e., “antigen binding sites,” (e.g., fragments, subsequences, complementarity determining regions (CDRs)) that retain capacity to bind antigen, including (i) a Fab fragment, a monovalent fragment consisting of the VL, VH, CL and CH1 domains; (ii) a F(ab′)2 fragment, a bivalent fragment comprising two Fab fragments linked by a disulfide bridge at the hinge region; (iii) a Fd fragment consisting of the VH and CH1 domains; (iv) a Fv fragment consisting of the VL and VH domains of a single arm of an antibody, (v) a dAb fragment (Ward et al., (1989) Nature 341:544-546), which consists of a VH domain; and (vi) an isolated complementarity determining region (CDR). Single chain antibodies are also included by reference in the term “antibody.”

Antibodies used in the immunoassays described herein preferably specifically bind Beta-2-glycoprotein 1. The term “specifically binds” is not intended to indicate that an antibody binds exclusively to its intended target since, as noted above, an antibody binds to any polypeptide displaying the epitope(s) to which the antibody binds. Rather, an antibody “specifically binds” if its affinity for its intended target is about 5-fold greater when compared to its affinity for a non-target molecule which does not display the appropriate epitope(s). Preferably the affinity of the antibody will be at least about 5 fold, preferably 10 fold, more preferably 25-fold, even more preferably 50-fold, and most preferably 100-fold or more, greater for a target molecule than its affinity for a non-target molecule. In preferred embodiments, Preferred antibodies bind with affinities of at least about 10⁷ M⁻¹, and preferably between about 10⁸ M⁻¹ to about 10⁹ M⁻¹, about 10⁹ M⁻¹ to about 10¹⁰ M⁻¹, or about 10¹⁰ M⁻¹ to about 10¹² M⁻¹.

Affinity is calculated as K_(d)=k_(off)/k_(on) (k_(off) is the dissociation rate constant, K_(on) is the association rate constant and K_(d) is the equilibrium constant). Affinity can be determined at equilibrium by measuring the fraction bound (r) of labeled ligand at various concentrations (c). The data are graphed using the Scatchard equation: r/c=K(n−r): where r=moles of bound ligand/mole of receptor at equilibrium; c=free ligand concentration at equilibrium; K=equilibrium association constant; and n=number of ligand binding sites per receptor molecule. By graphical analysis, r/c is plotted on the Y-axis versus r on the X-axis, thus producing a Scatchard plot. Antibody affinity measurement by Scatchard analysis is well known in the art. See, e.g., van Erp et al., J. Immunoassay 12: 425-43, 1991; Nelson and Griswold, Comput. Methods Programs Biomed. 27: 65-8, 1988.

The term “epitope” refers to an antigenic determinant capable of specific binding to an antibody. Epitopes usually consist of chemically active surface groupings of molecules such as amino acids or sugar side chains and usually have specific three dimensional structural characteristics, as well as specific charge characteristics. Conformational and nonconformational epitopes are distinguished in that the binding to the former but not the latter is lost in the presence of denaturing solvents.

Numerous publications discuss the use of phage display technology to produce and screen libraries of polypeptides for binding to a selected analyte. See, e.g, Cwirla et al., Proc. Natl. Acad. Sci. USA 87, 6378-82, 1990; Devlin et al., Science 249, 404-6, 1990, Scott and Smith, Science 249, 386-88, 1990; and Ladner et al., U.S. Pat. No. 5,571,698. A basic concept of phage display methods is the establishment of a physical association between DNA encoding a polypeptide to be screened and the polypeptide. This physical association is provided by the phage particle, which displays a polypeptide as part of a capsid enclosing the phage genome which encodes the polypeptide. The establishment of a physical association between polypeptides and their genetic material allows simultaneous mass screening of very large numbers of phage bearing different polypeptides. Phage displaying a polypeptide with affinity to a target bind to the target and these phage are enriched by affinity screening to the target. The identity of polypeptides displayed from these phage can be determined from their respective genomes. Using these methods a polypeptide identified as having a binding affinity for a desired target can then be synthesized in bulk by conventional means. See, e.g., U.S. Pat. No. 6,057,098, which is hereby incorporated in its entirety, including all tables, figures, and claims.

The antibodies that are generated by these methods may then be selected by first screening for affinity and specificity with the purified polypeptide of interest and, if required, comparing the results to the affinity and specificity of the antibodies with polypeptides that are desired to be excluded from binding. The screening procedure can involve immobilization of the purified polypeptides in separate wells of microtiter plates. The solution containing a potential antibody or groups of antibodies is then placed into the respective microtiter wells and incubated for about 30 min to 2 h. The microtiter wells are then washed and a labeled secondary antibody (for example, an anti-mouse antibody conjugated to alkaline phosphatase if the raised antibodies are mouse antibodies) is added to the wells and incubated for about 30 min and then washed. Substrate is added to the wells and a color reaction will appear where antibody to the immobilized polypeptide(s) are present.

The antibodies so identified may then be further analyzed for affinity and specificity in the assay design selected. In the development of immunoassays for a target protein, the purified target protein acts as a standard with which to judge the sensitivity and specificity of the immunoassay using the antibodies that have been selected. Because the binding affinity of various antibodies may differ; certain antibody pairs (e.g., in sandwich assays) may interfere with one another sterically, etc., assay performance of an antibody may be a more important measure than absolute affinity and specificity of an antibody.

Assay Correlations

The term “correlating” as used herein in reference to the use of biomarkers such as Beta-2-glycoprotein 1 refers to comparing the presence or amount of the biomarker(s) in a patient to its presence or amount in persons known to suffer from, or known to be at risk of, a given condition; or in persons known to be free of a given condition. Often, this takes the form of comparing an assay result in the form of a biomarker concentration to a predetermined threshold selected to be indicative of the occurrence or nonoccurrence of a disease or the likelihood of some future outcome.

Selecting a diagnostic threshold involves, among other things, consideration of the probability of disease, distribution of true and false diagnoses at different test thresholds, and estimates of the consequences of treatment (or a failure to treat) based on the diagnosis. For example, when considering administering a specific therapy which is highly efficacious and has a low level of risk, few tests are needed because clinicians can accept substantial diagnostic uncertainty. On the other hand, in situations where treatment options are less effective and more risky, clinicians often need a higher degree of diagnostic certainty. Thus, cost/benefit analysis is involved in selecting a diagnostic threshold.

Suitable thresholds may be determined in a variety of ways. For example, one recommended diagnostic threshold for the diagnosis of acute myocardial infarction using cardiac troponin is the 97.5^(th) percentile of the concentration seen in a normal population. Another method may be to look at serial samples from the same patient, where a prior “baseline” result is used to monitor for temporal changes in a biomarker level.

Population studies may also be used to select a decision threshold. Receiver Operating Characteristic (“ROC”) arose from the field of signal dectection therory developed during World War II for the analysis of radar images, and ROC analysis is often used to select a threshold able to best distinguish a “diseased” subpopulation from a “nondiseased” subpopulation. A false positive in this case occurs when the person tests positive, but actually does not have the disease. A false negative, on the other hand, occurs when the person tests negative, suggesting they are healthy, when they actually do have the disease. To draw a ROC curve, the true positive rate (TPR) and false positive rate (FPR) are determined as the decision threshold is varied continuously. Since TPR is equivalent with sensitivity and FPR is equal to 1−specificity, the ROC graph is sometimes called the sensitivity vs (1−specificity) plot. A perfect test will have an area under the ROC curve of 1.0; a random test will have an area of 0.5. A threshold is selected to provide an acceptable level of specificity and sensitivity.

In this context, “diseased” is meant to refer to a population having one characteristic (the presence of a disease or condition or the occurrence of some outcome) and “nondiseased” is meant to refer to a population lacking the characteristic. While a single decision threshold is the simplest application of such a method, multiple decision thresholds may be used. For example, below a first threshold, the absence of disease may be assigned with relatively high confidence, and above a second threshold the presence of disease may also be assigned with relatively high confidence. Between the two thresholds may be considered indeterminate. This is meant to be exemplary in nature only.

In addition to threshold comparisons, other methods for correlating assay results to a patient classification (occurrence or nonoccurrence of disease, likelihood of an outcome, etc.) include decision trees, rule sets, Bayesian methods, and neural network methods. These methods can produce probability values representing the degree to which a subject belongs to one classification out of a plurality of classifications.

Measures of test accuracy may be obtained as described in Fischer et al., Intensive Care Med. 29: 1043-51, 2003, and used to determine the effectiveness of a given biomarker. These measures include sensitivity and specificity, predictive values, likelihood ratios, diagnostic odds ratios, and ROC curve areas. The area under the curve (“AUC”) of a ROC plot is equal to the probability that a classifier will rank a randomly chosen positive instance higher than a randomly chosen negative one. The area under the ROC curve may be thought of as equivalent to the Mann-Whitney U test, which tests for the median difference between scores obtained in the two groups considered if the groups are of continuous data, or to the Wilcoxon test of ranks.

As discussed above, suitable tests may exhibit one or more of the following results on these various measures: a specificity of greater than 0.5, preferably at least 0.6, more preferably at least 0.7, still more preferably at least 0.8, even more preferably at least 0.9 and most preferably at least 0.95, with a corresponding sensitivity greater than 0.2, preferably greater than 0.3, more preferably greater than 0.4, still more preferably at least 0.5, even more preferably 0.6, yet more preferably greater than 0.7, still more preferably greater than 0.8, more preferably greater than 0.9, and most preferably greater than 0.95; a sensitivity of greater than 0.5, preferably at least 0.6, more preferably at least 0.7, still more preferably at least 0.8, even more preferably at least 0.9 and most preferably at least 0.95, with a corresponding specificity greater than 0.2, preferably greater than 0.3, more preferably greater than 0.4, still more preferably at least 0.5, even more preferably 0.6, yet more preferably greater than 0.7, still more preferably greater than 0.8, more preferably greater than 0.9, and most preferably greater than 0.95; at least 75% sensitivity, combined with at least 75% specificity; a ROC curve area of greater than 0.5, preferably at least 0.6, more preferably 0.7, still more preferably at least 0.8, even more preferably at least 0.9, and most preferably at least 0.95; an odds ratio different from 1, preferably at least about 2 or more or about 0.5 or less, more preferably at least about 3 or more or about 0.33 or less, still more preferably at least about 4 or more or about 0.25 or less, even more preferably at least about 5 or more or about 0.2 or less, and most preferably at least about 10 or more or about 0.1 or less; a positive likelihood ratio (calculated as sensitivity/(1−specificity)) of greater than 1, at least 2, more preferably at least 3, still more preferably at least 5, and most preferably at least 10; and or a negative likelihood ratio (calculated as (1−sensitivity)/specificity) of less than 1, less than or equal to 0.5, more preferably less than or equal to 0.3, and most preferably less than or equal to 0.1

Additional clinical indicia may be combined with the Beta-2-glycoprotein 1 assay result of the present invention. These include other biomarkers related to renal status. Examples include the following, which recite the common biomarker name, followed by the Swiss-Prot entry number for that biomarker or its parent: Actin (P68133); Adenosine deaminase binding protein (DPP4, P27487); Alpha-1-acid glycoprotein 1 (P02763); Alpha-1-microglobulin (P02760); Albumin (P02768); Angiotensinogenase (Renin, P00797); Annexin A2 (P07355); Beta-glucuronidase (P08236); B-2-microglobulin (P61679); Beta-galactosidase (P16278); BMP-7 (P18075); Brain natriuretic peptide (proBNP, BNP-32, NTproBNP; P16860); Calcium-binding protein Beta (S100-beta, PO4271); Carbonic anhydrase (Q16790); Casein Kinase 2 (P68400); Cathepsin B (P07858); Ceruloplasmin (P00450); Clusterin (P10909); Complement C3 (P01024); Cysteine-rich protein (CYR61, 000622); Cytochrome C (P99999); Epidermal growth factor (EGF, P01133); Endothelin-1 (P05305); Exosomal Fetuin-A (P02765); Fatty acid-binding protein, heart (FABP3, P05413); Fatty acid-binding protein, liver (P07148); Ferritin (light chain, P02793; heavy chain P02794); Fructose-1,6-biphosphatase (P09467); GRO-alpha (CXCL1, (P09341); Growth Hormone (P01241); Hepatocyte growth factor (P14210); Insulin-like growth factor I (P01343); Immunoglobulin G; Immunoglobulin Light Chains (Kappa and Lambda); Interferon gamma (P01308); Lysozyme (P61626); Interleukin-1alpha (P01583); Interleukin-2 (P60568); Interleukin-4 (P60568); Interleukin-9 (P15248); Interleukin-12p40 (P29460); Interleukin-13 (P35225); Interleukin-16 (Q14005); L1 cell adhesion molecule (P32004); Lactate dehydrogenase (P00338); Leucine Aminopeptidase (P28838); Meprin A-alpha subunit (Q16819); Meprin A-beta subunit (Q16820); Midkine (P21741); MIP2-alpha (CXCL2, P19875); MMP-2 (P08253); MMP-9 (P14780); Netrin-1 (095631); Neutral endopeptidase (P08473); Osteopontin (P10451); Renal papillary antigen 1 (RPA1); Renal papillary antigen 2 (RPA2); Retinol binding protein (P09455); Ribonuclease; S100 calcium-binding protein A6 (P06703); Serum Amyloid P Component (P02743); Sodium/Hydrogen exchanger isoform (NHE3, P48764); Spermidine/spermine N1-acetyltransferase (P21673); TGF-Beta1 (P01137); Transferrin (P02787); Trefoil factor 3 (TFF3, Q07654); Toll-Like protein 4 (000206); Total protein; Tubulointerstitial nephritis antigen (Q9UJW2); Uromodulin (Tamm-Horsfall protein, P07911).

For purposes of risk stratification, Adiponectin (Q15848); Alkaline phosphatase (P05186); Aminopeptidase N (P15144); CalbindinD28k (P05937); Cystatin C (P01034); 8 subunit of F1FO ATPase (P03928); Gamma-glutamyltransferase (P19440); GSTa (alpha-glutathione-S-transferase, P08263); GSTpi (Glutathione-S-transferase P; GST class-pi; P09211); IGFBP-1 (P08833); IGFBP-2 (P18065); IGFBP-6 (P24592); Integral membrane protein 1 (Itm1, P46977); Interleukin-6 (P05231); Interleukin-8 (P10145); Interleukin-18 (Q14116); IP-10 (10 kDa interferon-gamma-induced protein, P02778); IRPR (IFRD1, 000458); Isovaleryl-CoA dehydrogenase (IVD, P26440); I-TAC/CXCL11 (014625); Keratin 19 (P08727); Kim-1 (Hepatitis A virus cellular receptor 1, O43656); L-arginine:glycine amidinotransferase (P50440); Leptin (P41159); Lipocalin2 (NGAL, P80188); MCP-1 (P13500); MIG (Gamma-interferon-induced monokine Q07325); MIP-1a (P10147); MIP-3a (P78556); MIP-1beta (P13236); MIP-1d (Q16663); NAG (N-acetyl-beta-D-glucosaminidase, P54802); Organic ion transporter (OCT2, O15244); Osteoprotegerin (O14788); P8 protein (060356); Plasminogen activator inhibitor 1 (PAI-1, P05121); ProANP(1-98) (P01160); Protein phosphatase 1-beta (PPI-beta, P62140); Rab GDI-beta (P50395); Renal kallikrein (Q86U61); RT1.B-1 (alpha) chain of the integral membrane protein (Q5Y7A8); Soluble tumor necrosis factor receptor superfamily member 1A (sTNFR-I, P19438); Soluble tumor necrosis factor receptor superfamily member 1B (sTNFR-II, P20333); Tissue inhibitor of metalloproteinases 3 (TIMP-3, P35625); uPAR (Q03405) may be combined with the Beta-2-glycoprotein 1 assay result of the present invention.

Other clinical indicia which may be combined with the Beta-2-glycoprotein 1 assay result of the present invention includes demographic information (e.g., weight, sex, age, race), medical history (e.g., family history, type of surgery, pre-existing disease such as aneurism, congestive heart failure, preeclampsia, eclampsia, diabetes mellitus, hypertension, coronary artery disease, proteinuria, renal insufficiency, or sepsis, type of toxin exposure such as NSAIDs, cyclosporines, tacrolimus, aminoglycosides, foscarnet, ethylene glycol, hemoglobin, myoglobin, ifosfamide, heavy metals, methotrexate, radiopaque contrast agents, or streptozotocin), clinical variables (e.g., blood pressure, temperature, respiration rate), risk scores (APACHE score, PREDICT score, TIMI Risk Score for UA/NSTEMI, Framingham Risk Score), a urine total protein measurement, a glomerular filtration rate, an estimated glomerular filtration rate, a urine production rate, a serum or plasma creatinine concentration, a renal papillary antigen 1 (RPA1) measurement; a renal papillary antigen 2 (RPA2) measurement; a urine creatinine concentration, a fractional excretion of sodium, a urine sodium concentration, a urine creatinine to serum or plasma creatinine ratio, a urine specific gravity, a urine osmolality, a urine urea nitrogen to plasma urea nitrogen ratio, a plasma BUN to creatinine ratio, and/or a renal failure index calculated as urine sodium/(urine creatinine/plasma creatinine). Other measures of renal function which may be combined with the Beta-2-glycoprotein 1 assay result are described hereinafter and in Harrison's Principles of Internal Medicine, 17^(th) Ed., McGraw Hill, New York, pages 1741-1830, and Current Medical Diagnosis & Treatment 2008, 47^(th) Ed, McGraw Hill, New York, pages 785-815, each of which are hereby incorporated by reference in their entirety.

Combining assay results/clinical indicia in this manner can comprise the use of multivariate logistical regression, loglinear modeling, neural network analysis, n-of-m analysis, decision tree analysis, etc. This list is not meant to be limiting.

Diagnosis of Acute Renal Failure

As noted above, the terms “acute renal (or kidney) injury” and “acute renal (or kidney) failure” as used herein are defined in part in terms of changes in serum creatinine from a baseline value. Most definitions of ARF have common elements, including the use of serum creatinine and, often, urine output. Patients may present with renal dysfunction without an available baseline measure of renal function for use in this comparison. In such an event, one may estimate a baseline serum creatinine value by assuming the patient initially had a normal GFR. Glomerular filtration rate (GFR) is the volume of fluid filtered from the renal (kidney) glomerular capillaries into the Bowman's capsule per unit time. Glomerular filtration rate (GFR) can be calculated by measuring any chemical that has a steady level in the blood, and is freely filtered but neither reabsorbed nor secreted by the kidneys. GFR is typically expressed in units of ml/min:

${GFR} = \frac{{Urine}\mspace{14mu}{Concentration} \times {Urine}\mspace{14mu}{Flow}}{{Plasma}\mspace{14mu}{Concentration}}$

By normalizing the GFR to the body surface area, a GFR of approximately 75-100 ml/min per 1.73 m² can be assumed. The rate therefore measured is the quantity of the substance in the urine that originated from a calculable volume of blood.

There are several different techniques used to calculate or estimate the glomerular filtration rate (GFR or eGFR). In clinical practice, however, creatinine clearance is used to measure GFR. Creatinine is produced naturally by the body (creatinine is a metabolite of creatine, which is found in muscle). It is freely filtered by the glomerulus, but also actively secreted by the renal tubules in very small amounts such that creatinine clearance overestimates actual GFR by 10-20%. This margin of error is acceptable considering the ease with which creatinine clearance is measured.

Creatinine clearance (CCr) can be calculated if values for creatinine's urine concentration (U_(Cr)), urine flow rate (V), and creatinine's plasma concentration (P_(Cr)) are known. Since the product of urine concentration and urine flow rate yields creatinine's excretion rate, creatinine clearance is also said to be its excretion rate (U_(Cr)×V) divided by its plasma concentration. This is commonly represented mathematically as:

$C_{Cr} = \frac{U_{Cr} \times V}{P_{Cr}}$

Commonly a 24 hour urine collection is undertaken, from empty-bladder one morning to the contents of the bladder the following morning, with a comparative blood test then taken:

$C_{Cr} = \frac{U_{Cr} \times 24\text{-}{hour}\mspace{14mu}{volume}}{P_{Cr} \times 24 \times 60\mspace{14mu}{mins}}$

To allow comparison of results between people of different sizes, the CCr is often corrected for the body surface area (BSA) and expressed compared to the average sized man as ml/min/1.73 m2. While most adults have a BSA that approaches 1.7 (1.6-1.9), extremely obese or slim patients should have their CCr corrected for their actual BSA:

$C_{{Cr} - {corrected}} = \frac{C_{Cr} \times 1.73}{BSA}$

The accuracy of a creatinine clearance measurement (even when collection is complete) is limited because as glomerular filtration rate (GFR) falls creatinine secretion is increased, and thus the rise in serum creatinine is less. Thus, creatinine excretion is much greater than the filtered load, resulting in a potentially large overestimation of the GFR (as much as a twofold difference). However, for clinical purposes it is important to determine whether renal function is stable or getting worse or better. This is often determined by monitoring serum creatinine alone. Like creatinine clearance, the serum creatinine will not be an accurate reflection of GFR in the non-steady-state condition of ARF. Nonetheless, the degree to which serum creatinine changes from baseline will reflect the change in GFR. Serum creatinine is readily and easily measured and it is specific for renal function.

For purposes of determining urine output on a Urine output on a mL/kg/hr basis, hourly urine collection and measurement is adequate. In the case where, for example, only a cumulative 24-h output was available and no patient weights are provided, minor modifications of the RIFLE urine output criteria have been described. For example, Bagshaw et al., Nephrol. Dial. Transplant. 23: 1203-1210, 2008, assumes an average patient weight of 70 kg, and patients are assigned a RIFLE classification based on the following: <35 mL/h (Risk), <21 mL/h (Injury) or <4 mL/h (Failure).

Selecting a Treatment Regimen

Once a diagnosis is obtained, the clinician can readily select a treatment regimen that is compatible with the diagnosis, such as initiating renal replacement therapy, withdrawing delivery of compounds that are known to be damaging to the kidney, kidney transplantation, delaying or avoiding procedures that are known to be damaging to the kidney, modifying diuretic administration, initiating goal directed therapy, etc. The skilled artisan is aware of appropriate treatments for numerous diseases discussed in relation to the methods of diagnosis described herein. See, e.g., Merck Manual of Diagnosis and Therapy, 17th Ed. Merck Research Laboratories, Whitehouse Station, N.J., 1999. In addition, since the methods and compositions described herein provide prognostic information, the markers of the present invention may be used to monitor a course of treatment. For example, improved or worsened prognostic state may indicate that a particular treatment is or is not efficacious.

One skilled in the art readily appreciates that the present invention is well adapted to carry out the objects and obtain the ends and advantages mentioned, as well as those inherent therein. The examples provided herein are representative of preferred embodiments, are exemplary, and are not intended as limitations on the scope of the invention.

EXAMPLE 1 Contrast-Induced Nephropathy Sample Collection

The objective of this sample collection study is to collect samples of plasma and urine and clinical data from patients before and after receiving intravascular contrast media. Approximately 250 adults undergoing radiographic/angiographic procedures involving intravascular administration of iodinated contrast media are enrolled. To be enrolled in the study, each patient must meet all of the following inclusion criteria and none of the following exclusion criteria:

Inclusion Criteria

-   males and females 18 years of age or older; -   undergoing a radiographic/angiographic procedure (such as a CT scan     or coronary intervention) involving the intravascular administration     of contrast media; -   expected to be hospitalized for at least 48 hours after contrast     administration. -   able and willing to provide written informed consent for study     participation and to comply with all study procedures.     Exclusion Criteria -   renal transplant recipients; -   acutely worsening renal function prior to the contrast procedure; -   already receiving dialysis (either acute or chronic) or in imminent     need of dialysis at enrollment; -   expected to undergo a major surgical procedure (such as involving     cardiopulmonary bypass) or an additional imaging procedure with     contrast media with significant risk for further renal insult within     the 48 hrs following contrast administration; -   participation in an interventional clinical study with an     experimental therapy within the previous 30 days; -   known infection with human immunodeficiency virus (HIV) or a     hepatitis virus.

Immediately prior to the first contrast administration (and after any pre-procedure hydration), an EDTA anti-coagulated blood sample (10 mL) and a urine sample (10 mL) are collected from each patient. Blood and urine samples are then collected at 4 (±0.5), 8 (±1), 24 (±2) 48 (±2), and 72 (±2) hrs following the last administration of contrast media during the index contrast procedure. Blood is collected via direct venipuncture or via other available venous access, such as an existing femoral sheath, central venous line, peripheral intravenous line or hep-lock. These study blood samples are processed to plasma at the clinical site, frozen and shipped to Astute Medical, Inc., San Diego, Calif. The study urine samples are frozen and shipped to Astute Medical, Inc.

Serum creatinine is assessed at the site immediately prior to the first contrast administration (after any pre-procedure hydration) and at 4 (±0.5), 8 (±1), 24 (±2) and 48 (±2)), and 72 (±2) hours following the last administration of contrast (ideally at the same time as the study samples are obtained). In addition, each patient's status is evaluated through day 30 with regard to additional serum and urine creatinine measurements, a need for dialysis, hospitalization status, and adverse clinical outcomes (including mortality).

Prior to contrast administration, each patient is assigned a risk based on the following assessment: systolic blood pressure <80 mm Hg=5 points; intra-arterial balloon pump=5 points; congestive heart failure (Class III-IV or history of pulmonary edema)=5 points; age >75 yrs=4 points; hematocrit level <39% for men, <35% for women=3 points; diabetes=3 points; contrast media volume=1 point for each 100 mL; serum creatinine level >1.5 g/dL=4 points OR estimated GFR 40-60 mL/min/1.73 m²=2 points, 20-40 mL/min/1.73 m²=4 points, <20 mL/min/1.73 m²=6 points. The risks assigned are as follows: risk for CIN and dialysis: 5 or less total points=risk of CIN—7.5%, risk of dialysis—0.04%; 6-10 total points=risk of CIN—14%, risk of dialysis—0.12%; 11-16 total points=risk of CIN—26.1%, risk of dialysis—1.09%; >16 total points=risk of CIN—57.3%, risk of dialysis—12.8%.

EXAMPLE 2 Cardiac Surgery Sample Collection

The objective of this sample collection study is to collect samples of plasma and urine and clinical data from patients before and after undergoing cardiovascular surgery, a procedure known to be potentially damaging to kidney function. Approximately 900 adults undergoing such surgery are enrolled. To be enrolled in the study, each patient must meet all of the following inclusion criteria and none of the following exclusion criteria:

Inclusion Criteria

-   males and females 18 years of age or older; -   undergoing cardiovascular surgery; -   Toronto/Ottawa Predictive Risk Index for Renal Replacement risk     score of at least 2 (Wijeysundera et al., JAMA 297: 1801-9, 2007);     and -   able and willing to provide written informed consent for study     participation and to comply with all study procedures.     Exclusion Criteria -   known pregnancy; -   previous renal transplantation; -   acutely worsening renal function prior to enrollment (e.g., any     category of RIFLE criteria); -   already receiving dialysis (either acute or chronic) or in imminent     need of dialysis at enrollment; -   currently enrolled in another clinical study or expected to be     enrolled in another clinical study within 7 days of cardiac surgery     that involves drug infusion or a therapeutic intervention for AKI; -   known infection with human immunodeficiency virus (HIV) or a     hepatitis virus.

Within 3 hours prior to the first incision (and after any pre-procedure hydration), an EDTA anti-coagulated blood sample (10 mL), whole blood (3 mL), and a urine sample (35 mL) are collected from each patient. Blood and urine samples are then collected at 3 (±0.5), 6 (±0.5), 12 (±1), 24 (±2) and 48 (±2) hrs following the procedure and then daily on days 3 through 7 if the subject remains in the hospital. Blood is collected via direct venipuncture or via other available venous access, such as an existing femoral sheath, central venous line, peripheral intravenous line or hep-lock. These study blood samples are frozen and shipped to Astute Medical, Inc., San Diego, Calif. The study urine samples are frozen and shipped to Astute Medical, Inc.

EXAMPLE 3 Acutely Ill Subject Sample Collection

The objective of this study is to collect samples from acutely ill patients. Approximately 900 adults expected to be in the ICU for at least 48 hours will be enrolled. To be enrolled in the study, each patient must meet all of the following inclusion criteria and none of the following exclusion criteria:

Inclusion Criteria

-   males and females 18 years of age or older; -   Study population 1: approximately 300 patients that have at least     one of: -   shock (SBP<90 mmHg and/or need for vasopressor support to maintain     MAP>60 mmHg and/or documented drop in SBP of at least 40 mmHg); and -   sepsis; -   Study population 2: approximately 300 patients that have at least     one of: -   IV antibiotics ordered in computerized physician order entry (CPOE)     within 24 hours of enrollment; -   contrast media exposure within 24 hours of enrollment; -   increased Intra-Abdominal Pressure with acute decompensated heart     failure; and -   severe trauma as the primary reason for ICU admission and likely to     be hospitalized in the ICU for 48 hours after enrollment; -   Study population 3: approximately 300 patients -   expected to be hospitalized through acute care setting (ICU or ED)     with a known risk factor for acute renal injury (e.g. sepsis,     hypotension/shock (Shock=systolic BP<90 mmHg and/or the need for     vasopressor support to maintain a MAP>60 mmHg and/or a documented     drop in SBP>40 mmHg), major trauma, hemorrhage, or major surgery);     and/or expected to be hospitalized to the ICU for at least 24 hours     after enrollment.     Exclusion Criteria -   known pregnancy; -   institutionalized individuals; -   previous renal transplantation; -   known acutely worsening renal function prior to enrollment (e.g.,     any category of RIFLE criteria); -   received dialysis (either acute or chronic) within 5 days prior to     enrollment or in imminent need of dialysis at the time of     enrollment; -   known infection with human immunodeficiency virus (HIV) or a     hepatitis virus; -   meets only the SBP<90 mmHg inclusion criterion set forth above, and     does not have shock in the attending physician's or principal     investigator's opinion.

After providing informed consent, an EDTA anti-coagulated blood sample (10 mL) and a urine sample (25-30 mL) are collected from each patient. Blood and urine samples are then collected at 4 (±0.5) and 8 (±1) hours after contrast administration (if applicable); at 12 (±1), 24 (±2), and 48 (±2) hours after enrollment, and thereafter daily up to day 7 to day 14 while the subject is hospitalized. Blood is collected via direct venipuncture or via other available venous access, such as an existing femoral sheath, central venous line, peripheral intravenous line or hep-lock. These study blood samples are processed to plasma at the clinical site, frozen and shipped to Astute Medical, Inc., San Diego, Calif. The study urine samples are frozen and shipped to Astute Medical, Inc.

EXAMPLE 4 Beta-2-Glycoprotein 1 Immunoassay

The Beta-2-glycoprotein 1 analyte is measured using standard sandwich enzyme immunoassay techniques. A first antibody which binds the analyte is immobilized in wells of a 96 well polystyrene microplate. Analyte standards and test samples are pipetted into the appropriate wells and any analyte present is bound by the immobilized antibody. After washing away any unbound substances, a horseradish peroxidase-conjugated second antibody which binds the analyte is added to the wells, thereby forming sandwich complexes with the analyte (if present) and the first antibody. Following a wash to remove any unbound antibody-enzyme reagent, a substrate solution comprising tetramethylbenzidine and hydrogen peroxide is added to the wells. Color develops in proportion to the amount of analyte present in the sample. The color development is stopped and the intensity of the color is measured at 540 nm or 570 nm. An analyte concentration is assigned to the test sample by comparison to a standard curve determined from the analyte standards.

EXAMPLE 5 Apparently Healthy Donor and Chronic Disease Patient Samples

Human urine samples from donors with no known chronic or acute disease (“Apparently Healthy Donors”) were purchased from two vendors (Golden West Biologicals, Inc., 27625 Commerce Center Dr., Temecula, Calif. 92590 and Virginia Medical Research, Inc., 915 First Colonial Rd., Virginia Beach, Va. 23454). The urine samples were shipped and stored frozen at less than −20° C. The vendors supplied demographic information for the individual donors including gender, race (Black/White), smoking status and age.

Human urine samples from donors with various chronic diseases (“Chronic Disease Patients”) including congestive heart failure, coronary artery disease, chronic kidney disease, chronic obstructive pulmonary disease, diabetes mellitus and hypertension were purchased from Virginia Medical Research, Inc., 915 First Colonial Rd., Virginia Beach, Va. 23454. The urine samples were shipped and stored frozen at less than −20 degrees centigrade. The vendor provided a case report form for each individual donor with age, gender, race (Black/White), smoking status and alcohol use, height, weight, chronic disease(s) diagnosis, current medications and previous surgeries.

EXAMPLE 6 Use of Beta-2-Glycoprotein 1 as a Marker for Evaluating Renal Status in Patients at RIFLE Stage 0

Patients from the intensive care unit (ICU) were classified by kidney status as non-injury (0), risk of injury (R), injury (I), and failure (F) according to the maximum stage reached within 7 days of enrollment as determined by the RIFLE criteria.

Two cohorts were defined as (Cohort 1) patients that did not progress beyond stage 0, and (Cohort 2) patients that reached stage R, I, or F within 10 days. To address normal marker fluctuations that occur within patients at the ICU and thereby assess utility for monitoring AKI status, marker levels in urine samples collected for Cohort 1. Beta-2-glycoprotein 1 concentrations were measured in urine samples collected from a subject at 0, 24 hours, and 48 hours prior to reaching stage R, I or F in Cohort 2. In the following tables, the time “prior max stage” represents the time at which a sample is collected, relative to the time a particular patient reaches the lowest disease stage as defined for that cohort, binned into three groups which are +/−12 hours. For example, 24 hr prior for this example (0 vs R, I, F) would mean 24 hr (+/−12 hours) prior to reaching stage R (or I if no sample at R, or F if no sample at R or I).

Beta-2-glycoprotein 1 was measured by standard immunoassay methods using commercially available assay reagents. Concentrations are expressed in the following examples as μg/mL. A receiver operating characteristic (ROC) curve was generated for Beta-2-glycoprotein 1 and the area under each ROC curve (AUC) was determined. Patients in Cohort 2 were also separated according to the reason for adjudication to stage R, I, or F as being based on serum creatinine measurements, being based on urine output, or being based on either serum creatinine measurements or urine output. That is, for those patients adjudicated to stage R, I, or F on the basis of serum creatinine measurements alone, the stage 0 cohort may have included patients adjudicated to stage R, I, or F on the basis of urine output; for those patients adjudicated to stage R, I, or F on the basis of urine output alone, the stage 0 cohort may have included patients adjudicated to stage R, I, or F on the basis of serum creatinine measurements; and for those patients adjudicated to stage R, I, or F on the basis of serum creatinine measurements or urine output, the stage 0 cohort contains only patients in stage 0 for both serum creatinine measurements and urine output. Also, for those patients adjudicated to stage R, I, or F on the basis of serum creatinine measurements or urine output, the adjudication method which yielded the most severe RIFLE stage was used.

The following descriptive statistics were obtained:

-   sCr or UO

0 hr prior 24 hr prior 48 hr prior max stage max stage max stage Cohort Cohort Cohort Cohort Cohort Cohort 1 2 1 2 1 2 median 0.250 0.351 0.250 0.443 0.250 0.314 average 0.352 0.442 0.352 0.521 0.352 0.367 stdev 0.321 0.355 0.321 0.346 0.321 0.343 p (t-test) 0.154 0.005 0.892 min 0.005 0.014 0.005 0.005 0.005 0.044 max 1.3 1.3 1.3 1.3 1.3 1.13 n 192 31 192 35 192 8

-   sCr only

0 hr prior 24 hr prior 48 hr prior max stage max stage max stage Cohort Cohort Cohort Cohort Cohort Cohort 1 2 1 2 1 2 median 0.305 0.279 0.305 0.398 0.305 0.544 average 0.389 0.507 0.389 0.529 0.389 0.526 stdev 0.321 0.492 0.321 0.494 0.321 0.211 p (t-test) 0.194 0.101 0.396 min 0.005 0.014 0.005 0.005 0.005 0.277 max 1.3 1.3 1.3 1.3 1.3 0.741 n 301 14 301 16 301 4

-   Urine output only

0 hr prior 24 hr prior 48 hr prior max stage max stage max stage Cohort Cohort Cohort Cohort Cohort Cohort 1 2 1 2 1 2 median 0.221 0.429 0.221 0.486 0.221 0.281 average 0.337 0.530 0.337 0.604 0.337 0.453 stdev 0.316 0.362 0.316 0.329 0.316 0.469 p (t-test) 0.005 <0.001 0.262 min 0.005 0.095 0.005 0.103 0.005 0.044 max 1.3 1.3 1.3 1.25 1.3 1.3 n 137 27 137 28 137 11

In the following tables, the ability to distinguish cohort 1 (subjects remaining in RIFLE 0) from Cohort 2 (subjects progressing to RIFLE R, I or F) was determined using ROC analysis. SE is the standard error of the AUC, n is the number of sample or individual patients (“pts,” as indicated). Standard errors were calculated as described in Hanley, J. A., and McNeil, B. J., The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology (1982) 143: 29-36; p values were calculated with a two-tailed Z-test.

-   Cohort 1 v Cohort 2, adjudicated on serum creatinine measurements or     urine output

Time prior max stage AUC SE n_(Cohort 1) n_(Cohort 2) p  0 hours 0.586 0.057 192 samples, 31 pts 0.134 57 pts 24 hours 0.658 0.054 192 35 pts 0.003 48 hours 0.523 0.106 192  8 pts 0.827

-   Cohort 1 v Cohort 2, adjudicated on serum creatinine

Time prior max stage AUC SE n_(Cohort 1) n_(Cohort 2) p  0 hours 0.519 0.080 301 samples, 14 pts 0.813 91 pts 24 hours 0.540 0.076 301 16 pts 0.598 48 hours 0.696 0.148 301  4 pts 0.187

-   Cohort 1 v Cohort 2, adjudicated on urine output

Time prior max stage AUC SE n_(Cohort 1) n_(Cohort 2) p  0 hours 0.703 0.060 137 samples, 27 pts 0.001 36 pts 24 hours 0.756 0.056 137 28 pts <0.001 48 hours 0.531 0.092 137 11 pts 0.738

Various threshold (or “cutoff”) Beta-2-glycoprotein 1 concentrations were selected, and the associated sensitivity and specificity for distinguishing cohort 1 from cohort 2, as shown in the following tables. OR is the odds ratio calculated for the particular cutoff concentration, and 95% CI is the confidence interval for the odds ratio:

0 hr prior max stage

Cutoff concentration sens spec OR 95% CI sCr or UO 0.20 74% 44% 2.3 1.0 5.4 0.50 39% 75% 1.9 0.9 4.2 sCr only 0.63 43% 81% 3.3 1.1 9.8 1.01 29% 93% 5.3 1.5 18 UO only 0.13 96% 31% 11.9 1.6 91 0.22 85% 52% 6.2 2.0 19 0.31 70% 62% 3.9 1.6 9.5 0.47 48% 78% 3.3 1.4 7.8 0.62 33% 87% 3.3 1.3 8.5

24 hr prior max stage

Cutoff concentration sens spec OR 95% CI sCr or UO 0.31 77% 58% 4.7 2.0 11 0.38 66% 67% 3.8 1.8 8.2 sCr only 0.54 44% 74% 2.2 0.8 6.1 0.91 31% 91% 4.8 1.6 15 UO only 0.26 89% 53% 9.5 2.7 33 0.31 86% 61% 9.2 3.0 28 0.35 79% 65% 6.8 2.6 18 0.41 68% 72% 5.5 2.3 13 0.68 43% 89% 6.1 2.4 15

48 hr prior max stage

Cutoff concentration sens spec OR 95% CI sCr or UO 0.28 63% 55% 2.0 0.5 8.7 0.34 50% 62% 1.6 0.4 6.7 sCr only 0.43 75% 63% 5.2 0.5 51 0.65 50% 82% 4.7 0.6 34 UO only 0.14 89% 30% 3.4 0.4 28 0.28 78% 55% 4.3 0.9 21 0.32 67% 62% 3.2 0.8 13 0.65 56% 88% 9.6 2.4 38 0.71 44% 90% 7.1 1.8 28

EXAMPLE 7 Use of Beta-2-Glycoprotein 1 as a Marker for Evaluating Renal Status in Patients at RIFLE Stages 0 and R

Patients were classified and analyzed as described in Example 6. However, patients that reached stage R but did not progress to stage I or F were grouped with patients from non-injury stage 0 in Cohort 1. Cohort 2 in this example included only patients that progressed to stage I or F. Beta-2-glycoprotein 1 concentrations in urine samples were included for Cohort 1. Beta-2-glycoprotein 1 concentrations in urine samples collected within 0, 24, and 48 hours of reaching stage I or F were included for Cohort 2.

The following descriptive statistics were obtained:

-   sCr or UO

0 hr prior 24 hr prior 48 hr prior max stage max stage max stage Cohort Cohort Cohort Cohort Cohort Cohort 1 2 1 2 1 2 median 0.246 0.583 0.246 0.749 0.246 0.659 average 0.345 0.638 0.345 0.712 0.345 0.599 stdev 0.309 0.333 0.309 0.376 0.309 0.428 p (t-test) <0.001 <0.001 0.017 min 0.005 0.048 0.005 0.030 0.005 0.074 max 1.3 1.24 1.3 1.3 1.3 1.3 n 291 15 291 19 291 9

-   sCr only

0 hr prior 24 hr prior 48 hr prior max stage max stage max stage Cohort Cohort Cohort Cohort Cohort Cohort 1 2 1 2 1 2 median 0.296 0.654 0.296 0.853 0.296 0.747 average 0.392 0.734 0.392 0.793 0.392 0.775 stdev 0.331 0.304 0.331 0.466 0.331 0.512 p (t-test) 0.075 0.008 0.048 min 0.005 0.479 0.005 0.030 0.005 0.277 max 1.3 1.07 1.3 1.3 1.3 1.3 n 345 3 345 5 345 3

-   Urine output only

0 hr prior 24 hr prior 48 hr prior max stage max stage max stage Cohort Cohort Cohort Cohort Cohort Cohort 1 2 1 2 1 2 median 0.244 0.588 0.244 0.734 0.244 0.659 average 0.345 0.660 0.345 0.702 0.345 0.611 stdev 0.309 0.356 0.309 0.358 0.309 0.434 p (t-test) <0.001 <0.001 0.014 min 0.005 0.048 0.005 0.034 0.005 0.074 max 1.3 1.3 1.3 1.25 1.3 1.3 n 216 15 216 16 216 9

In the following tables, the ability to distinguish cohort 1 (subjects remaining in RIFLE 0 or R) from Cohort 2 (subjects progressing to RIFLE I or F) was determined using ROC analysis.

-   Cohort 1 v Cohort 2, adjudicated on serum creatinine measurements or     urine output

Time prior max stage AUC SE n_(Cohort 1) n_(Cohort 2) p  0 hours 0.768 0.073 291 samples, 15 pts <0.001 89 pts 24 hours 0.769 0.065 291 19 pts <0.001 48 hours 0.691 0.099 291  9 pts 0.055

-   Cohort 1 v Cohort 2, adjudicated on serum creatinine

Time prior max stage AUC SE n_(Cohort 1) n_(Cohort 2) p  0 hours 0.818 0.150 345 samples, 3 pts 0.034 106 pts 24 hours 0.736 0.129 345 5 pts 0.067 48 hours 0.771 0.161 345 3 pts 0.091

-   Cohort 1 v Cohort 2, adjudicated on urine output

Time prior max stage AUC SE n_(Cohort 1) n_(Cohort 2) p  0 hours 0.780 0.072 216 samples, 15 pts <0.001 60 pts 24 hours 0.791 0.069 216 16 pts <0.001 48 hours 0.692 0.100 216  9 pts 0.054

Various threshold (or “cutoff”) Beta-2-glycoprotein 1 concentrations were selected, and the associated sensitivity and specificity for distinguishing cohort 1 from cohort 2, as shown in the following tables. OR is the odds ratio calculated for the particular cutoff concentration, and 95% CI is the confidence interval for the odds ratio:

0 hr prior max stage

Cutoff concentration sens spec OR 95% CI sCr or UO 0.31 93% 59% 20 2.6 156 0.42 80% 69% 9.1 2.5 33 0.47 73% 76% 8.7 2.7 28 0.62 47% 85% 5.0 1.7 15 sCr only 0.47 100%  69% 25 2.1 287 0.65 67% 81% 8.8 0.8 98 UO only 0.31 93% 60% 21 2.7 164 0.42 80% 71% 9.7 2.7 36 0.51 73% 79% 10 3.2 34 0.58 60% 83% 7.3 2.4 22

24 hr prior max stage

Cutoff concentration sens spec OR 95% CI sCr or UO 0.26 89% 52% 9.2 2.1 40 0.44 79% 72% 9.7 3.1 30 0.62 68% 85% 12 4.5 35 0.72 63% 89% 13 4.9 36 sCr only 0.82 80% 88% 29 3.1 264 0.91 40% 90% 6.3 1.0 39 UO only 0.26 94% 53% 17 2.2 129 0.44 81% 74% 12 3.3 44 0.62 63% 87% 11 3.6 32 0.71 56% 90% 11 3.8 33

48 hr prior max stage

Cutoff concentration sens spec OR 95% CI sCr or UO 0.28 78% 54% 4.0 0.8 20 0.34 67% 62% 3.2 0.8 13 0.65 56% 87% 8.1 2.1 31 0.71 44% 88% 5.9 1.5 23 sCr only 0.28 100%  47% 6.6 0.7 64 0.74 67% 86% 12 1.1 133 UO only 0.28 78% 55% 4.3 0.9 21 0.32 67% 62% 3.2 0.8 13 0.65 56% 88% 9.6 2.4 38 0.71 44% 90% 7.1 1.8 28

EXAMPLE 8 Use of Beta-2-Glycoprotein 1 as a Marker for Evaluating Renal Status in Patients Progressing from Stage R to Stages I and F

Patients were classified and analyzed as described in Example 6, but only those patients that reached Stage R were included in this example. Cohort 1 contained patients that reached stage R but did not progress to stage I or F within 10 days, and Cohort 2 included only patients that progressed to stage I or F. Beta-2-glycoprotein 1 concentrations in urine samples collected within 12 hours of reaching stage R were included in the analysis for both Cohort 1 and 2.

The following descriptive statistics were obtained:

sCR or UO sCR only UO only Cohort Cohort Cohort Cohort Cohort Cohort 1 2 1 2 1 2 median 0.227 0.567 0.198 0.853 0.348 0.395 average 0.363 0.628 0.427 0.851 0.412 0.477 stdev 0.345 0.425 0.466 0.512 0.338 0.292 p (t-test) 0.046 0.112 0.642 min 0.014 0.053 0.014 0.053 0.095 0.217 max 1.3 1.3 1.3 1.3 1.3 1.11 n 27 12 13 5 20 8

In the following tables, the ability to distinguish cohort 1 (subjects remaining in RIFLE R) from Cohort 2 (subjects progressing to RIFLE I or F) was determined using ROC analysis.

-   Cohort 1 v Cohort 2, adjudicated on serum creatinine measurements or     urine output

AUC SE n_(Cohort 1) n_(Cohort 2) p 0.701 0.096 27 pts 12 pts 0.037

-   Cohort 1 v Cohort 2, adjudicated on serum creatinine

AUC SE n_(Cohort 1) n_(Cohort 2) p 0.708 0.148 13 pts 5 pts 0.160

-   Cohort 1 v Cohort 2, adjudicated on urine output

AUC SE n_(Cohort 1) n_(Cohort 2) p 0.619 0.123 20 pts 8 pts 0.333

Various threshold (or “cutoff”) Beta-2-glycoprotein 1 concentrations were selected, and the associated sensitivity and specificity for distinguishing cohort 1 from cohort 2, as shown in the following tables. OR is the odds ratio calculated for the particular cutoff concentration, and 95% CI is the confidence interval for the odds ratio:

Cutoff concentration sens spec OR 95% CI sCr or UO 0.21 92% 44% 8.8 1.0 78 0.26 83% 56% 6.3 1.1 34 0.46 58% 81% 6.2 1.4 28 0.65 42% 89% 5.7 1.1 30 sCr only 0.64 80% 77% 13 1.0 170 0.85 40% 92% 8.0 0.5 121 UO only 0.26 88% 45% 5.7 0.6 56 0.46 50% 80% 4.0 0.7 23

EXAMPLE 9 Evaluation of Beta-2-Glycoprotein 1 as a Marker in an ICU Patient Population

Patients from the intensive care unit (ICU) were enrolled in the following study. Each patient was classified by kidney status as non-injury (0), risk of injury (R), injury (I), and failure (F) according to the maximum stage reached within 7 days of enrollment as determined by the RIFLE criteria. EDTA anti-coagulated blood samples (10 mL) and a urine samples (25-30 mL) were collected from each patient at enrollment, 4 (±0.5) and 8 (±1) hours after contrast administration (if applicable); at 12 (±1), 24 (±2), and 48 (±2) hours after enrollment, and thereafter daily up to day 7 to day 14 while the subject is hospitalized. Beta-2-glycoprotein 1 was measured by standard immunoassay methods using commercially available assay reagents in the urine samples and the plasma component of the blood samples collected.

Two cohorts were defined as described in the introduction to each of the following tables. In the following tables, the time “prior max stage” represents the time at which a sample is collected, relative to the time a particular patient reaches the lowest disease stage as defined for that cohort, binned into three groups which are +/−12 hours. For example, “24 hr prior” which uses 0 vs R, I, F as the two cohorts would mean 24 hr (+/−12 hours) prior to reaching stage R (or I if no sample at R, or F if no sample at R or I).

A receiver operating characteristic (ROC) curve was generated for Beta-2-glycoprotein 1 and the area under each ROC curve (AUC) was determined. Patients in Cohort 2 were also separated according to the reason for adjudication to cohort 2 as being based on serum creatinine measurements (sCr), being based on urine output (UO), or being based on either serum creatinine measurements or urine output. Using the same example discussed above (0 vs R, I, F), for those patients adjudicated to stage R, I, or F on the basis of serum creatinine measurements alone, the stage 0 cohort may have included patients adjudicated to stage R, I, or F on the basis of urine output; for those patients adjudicated to stage R, I, or F on the basis of urine output alone, the stage 0 cohort may have included patients adjudicated to stage R, I, or F on the basis of serum creatinine measurements; and for those patients adjudicated to stage R, I, or F on the basis of serum creatinine measurements or urine output, the stage 0 cohort contains only patients in stage 0 for both serum creatinine measurements and urine output. Also, in the data for patients adjudicated on the basis of serum creatinine measurements or urine output, the adjudication method which yielded the most severe RIFLE stage was used.

The ability to distinguish cohort 1 from Cohort 2 was determined using ROC analysis. SE is the standard error of the AUC, n is the number of sample or individual patients (“pts,” as indicated). Standard errors were calculated as described in Hanley, J. A., and McNeil, B. J., The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology (1982) 143: 29-36; p values were calculated with a two-tailed Z-test, and are reported as p<0.05 in tables 1-4 and p<0.10 in tables 5-6. An AUC<0.5 is indicative of a negative going marker for the comparison, and an AUC>0.5 is indicative of a positive going marker for the comparison.

Various Beta-2-glycoprotein 1 threshold (or “cutoff”) concentrations were selected, and the associated sensitivity and specificity for distinguishing cohort 1 from cohort 2 were determined. OR is the odds ratio calculated for the particular cutoff concentration, and 95% CI is the confidence interval for the odds ratio.

TABLE 1 Comparison of marker levels in urine samples collected for Cohort 1 (patients that did not progress beyond RIFLE stage 0) and in urine samples collected from subjects at 0, 24 hours, and 48 hours prior to reaching stage R, I or F in Cohort 2. 0 hr prior to AKI stage 24 hr prior to AKI stage 48 hr prior to AKI stage sCr or UO Cohort 1 Cohort 2 Cohort 1 Cohort 2 Cohort 1 Cohort 2 Median 189 241 189 234 189 178 Average 309 522 309 492 309 303 Stdev 398 860 398 931 398 354 p(t-test) 0.0010 0.0048 0.92 Min 12.8 26.5 12.8 20.1 12.8 29.5 Max 4180 5560 4180 6150 4180 1840 n (Samp) 365 75 365 89 365 41 n (Patient) 196 75 196 89 196 41 0 hr prior to AKI stage 24 hr prior to AKI stage 48 hr prior to AKI stage sCr only Cohort 1 Cohort 2 Cohort 1 Cohort 2 Cohort 1 Cohort 2 Median 209 217 209 250 209 239 Average 368 750 368 689 368 549 Stdev 535 1460 535 1170 535 1250 p(t-test) 8.3E−4 0.0011 0.13 Min 12.8 26.5 12.8 33.7 12.8 32.1 Max 5840 6840 5840 5960 5840 6150 n (Samp) 754 28 754 37 754 23 n (Patient) 295 28 295 37 295 23 0 hr prior to AKI stage 24 hr prior to AKI stage 48 hr prior to AKI stage UO only Cohort 1 Cohort 2 Cohort 1 Cohort 2 Cohort 1 Cohort 2 Median 192 273 192 268 192 236 Average 314 562 314 535 314 438 Stdev 361 848 361 830 361 604 p(t-test) 2.2E−4 5.8E−4 0.077 Min 12.8 63.7 12.8 20.1 12.8 29.5 Max 3140 5560 3140 6150 3140 3160 n (Samp) 296 65 296 75 296 35 n (Patient) 132 65 132 75 132 35 0 hr prior to AKI stage 24 hr prior to AKI stage 48 hr prior to AKI stage sCr or UO sCr only UO only sCr or UO sCr only UO only sCr or UO sCr only UO only AUC 0.58 0.52 0.63 0.56 0.57 0.60 0.49 0.49 0.55 SE 0.037 0.056 0.040 0.035 0.050 0.038 0.048 0.062 0.053 P 0.032 0.74 0.0012 0.080 0.19 0.0060 0.87 0.83 0.34 nCohort 1 365 754 296 365 754 296 365 754 296 nCohort 2 75 28 65 89 37 75 41 23 35 Cutoff 1 146 124 176 131 140 165 109 99.8 148 Sens 1 71% 71% 71% 71% 70% 71% 71% 74% 71% Spec 1 39% 27% 44% 33% 32% 42% 27% 20% 39% Cutoff 2 121 85.0 144 113 95.2 127 79.5 74.7 109 Sens 2 80% 82% 80% 81% 81% 80% 80% 83% 80% Spec 2 31% 15% 38% 27% 19% 32% 17% 14% 25% Cutoff 3 74.7 55.6 113 63.9 54.9 87.1 51.4 46.3 56.1 Sens 3 91% 93% 91% 91% 92% 91% 90% 91% 91% Spec 3 16%  7% 25% 10%  7% 17%  7% 5%  7% Cutoff 4 298 331 305 298 331 305 298 331 305 Sens 4 37% 32% 42% 36% 46% 43% 32% 35% 34% Spec 4 70% 70% 70% 70% 70% 70% 70% 70% 70% Cutoff 5 425 526 451 425 526 451 425 526 451 Sens 5 29% 29% 32% 30% 38% 37% 20% 22% 29% Spec 5 80% 80% 80% 80% 80% 80% 80% 80% 80% Cutoff 6 700 733 700 700 733 700 700 733 700 Sens 6 15% 14% 18% 15% 16% 19% 10% 13% 14% Spec 6 93% 90% 94% 93% 90% 94% 93% 90% 94% OR Quart 2 1.5 0.74 2.6 1.3 0.99 1.9 1.0 1.4 0.85 p Value 0.33 0.58 0.050 0.50 0.99 0.12 0.98 0.55 0.77 95% CI of 0.68 0.25 1.00 0.63 0.37 0.84 0.40 0.44 0.29 OR Quart2 3.1 2.2 6.6 2.6 2.7 4.2 2.5 4.6 2.5 OR Quart 3 1.8 0.62 3.2 1.3 0.87 1.5 1.0 0.80 0.99 0 hr prior to AKI stage 24 hr prior to AKI stage 48 hr prior to AKI stage sCr or UO sCr only UO only sCr or UO sCr only UO only sCr or UO sCr only UO only p Value 0.14 0.40 0.014 0.48 0.78 0.31 1.0 0.74 0.98 95% CI of 0.83 0.20 1.3 0.64 0.31 0.67 0.40 0.21 0.35 OR Quart3 3.7 1.9 8.0 2.6 2.4 3.5 2.5 3.0 2.8 OR Quart 4 2.0 1.1 4.0 2.0 1.8 3.3 1.1 1.4 1.6 p Value 0.072 0.81 0.0026 0.038 0.20 0.0021 0.80 0.55 0.36 95% CI of 0.94 0.42 1.6 1.0 0.74 1.5 0.46 0.44 0.60 OR Quart4 4.1 3.0 9.9 3.9 4.4 7.2 2.8 4.6 4.1

TABLE 2 Comparison of marker levels in urine samples collected for Cohort 1 (patients that did not progress beyond RIFLE stage 0 or R) and in urine samples collected from subjects at 0, 24 hours, and 48 hours prior to reaching stage I or F in Cohort 2. 0 hr prior to AKI stage 24 hr prior to AKI stage 48 hr prior to AKI stage sCr or UO Cohort 1 Cohort 2 Cohort 1 Cohort 2 Cohort 1 Cohort 2 Median 192 345 192 700 192 213 Average 346 447 346 873 346 355 Stdev 524 364 524 1240 524 333 p (t-test) 0.24 6.4E−9 0.93 Min 12.8 24.1 12.8 47.3 12.8 24.6 Max 5960 1670 5960 6150 5960 1100 n (Samp) 688 38 688 47 688 26 n (Patient) 283 38 283 47 283 26 0 hr prior to AKI stage 24 hr prior to AKI stage 48 hr prior to AKI stage sCr only Cohort 1 Cohort 2 Cohort 1 Cohort 2 Cohort 1 Cohort 2 Median 209 552 209 700 209 566 Average 393 565 393 783 393 942 Stdev 603 343 603 1040 603 1820 p (t-test) 0.42 0.023 0.0020 Min 12.8 181 12.8 55.1 12.8 32.1 Max 6150 1240 6150 4000 6150 6840 n (Samp) 897 8 897 13 897 13 n (Patient) 335 8 335 13 335 13 0 hr prior to AKI stage 24 hr prior to AKI stage 48 hr prior to AKI stage UO only Cohort 1 Cohort 2 Cohort 1 Cohort 2 Cohort 1 Cohort 2 Median 199 363 199 595 199 239 Average 358 452 358 924 358 395 Stdev 535 373 535 1310 535 326 p (t-test) 0.31 2.2E−8 0.75 Min 12.8 24.1 12.8 47.3 12.8 24.6 Max 5960 1670 5960 6150 5960 1100 n (Samp) 555 35 555 41 555 22 n (Patient) 202 35 202 41 202 22 0 hr prior to AKI stage 24 hr prior to AKI stage 48 hr prior to AKI stage sCr or UO sCr only UO only sCr or UO sCr only UO only sCr or UO sCr only UO only AUC 0.65 0.75 0.63 0.69 0.64 0.71 0.52 0.58 0.59 SE 0.050 0.10 0.052 0.044 0.084 0.047 0.058 0.083 0.065 p 0.0030 0.015 0.012 9.6E−6 0.086 6.2E−6 0.68 0.33 0.19 nCohort 1 688 897 555 688 897 555 688 897 555 nCohort 2 38 8 35 47 13 41 26 13 22 Cutoff 1 211 326 211 249 180 261 109 109 165 Sens 1 71%  75% 71% 70% 77% 71% 73% 77% 73% Spec 1 55%  68% 52% 62% 42% 62% 24% 23% 39% Cutoff 2 162 269 162 131 95.2 170 99.8 107 147 Sens 2 82%  88% 80% 81% 85% 80% 81% 85% 82% Spec 2 41%  61% 39% 31% 19% 40% 22% 22% 36% Cutoff 3 97.4 181 97.4 86.1 66.1 116 46.3 46.3 90.6 Sens 3 92% 100% 91% 91% 92% 90% 92% 92% 91% Spec 3 21%  42% 19% 18% 11% 25%  6%  5% 17% Cutoff 4 307 353 322 307 353 322 307 353 322 Sens 4 53%  62% 51% 57% 62% 61% 35% 54% 41% Spec 4 70%  70% 70% 70% 70% 70% 70% 70% 70% Cutoff 5 468 570 487 468 570 487 468 570 487 Sens 5 39%  50% 40% 55% 62% 54% 35% 46% 36% Spec 5 80%  80% 80% 80% 80% 80% 80% 80% 80% Cutoff 6 700 784 700 700 784 700 700 784 700 Sens 6 11%  12% 11% 34% 15% 37% 15% 15% 14% Spec 6 92%  90% 92% 92% 90% 92% 92% 90% 92% OR Quart 2 1.2 >1.0 0.99 0.85 0.66 0.79 0.49 0 1.0 p Value 0.77 <1.00 0.99 0.77 0.65 0.74 0.25 na 1.0 95% CI of 0.36 >0.062 0.28 0.28 0.11 0.21 0.14 na 0.25 OR Quart2 4.0 na 3.5 2.6 4.0 3.0 1.6 na 4.1 OR Quart 3 2.1 >3.0 1.9 0.99 0 1.9 0.61 0.20 1.5 p Value 0.20 <0.34 0.28 0.99 na 0.28 0.40 0.14 0.52 95% CI of 0.69 >0.31 0.61 0.34 na 0.61 0.20 0.023 0.42 OR Quart3 6.1 na 5.7 2.9 na 5.7 1.9 1.7 5.5 OR Quart 4 3.6 >4.1 3.4 4.3 2.7 5.3 1.1 1.4 2.0 p Value 0.013 <0.21 0.019 8.3E−4 0.14 0.0011 0.81 0.57 0.25 95% CI of 1.3 >0.45 1.2 1.8 0.71 1.9 0.42 0.44 0.60 OR Quart4 10 na 9.7 10 10 14 3.0 4.5 6.9

TABLE 3 Comparison of marker levels in urine samples collected within 12 hours of reaching stage R for Cohort 1 (patients that reached, but did not progress beyond, RIFLE stage R) and for Cohort 2 (patients that reached RIFLE stage I or F). sCr or UO sCr only UO only Cohort 1 Cohort 2 Cohort 1 Cohort 2 Cohort 1 Cohort 2 Median 210 266 166 700 233 257 Average 499 648 484 1390 535 623 Stdev 919 1080 827 2100 958 1160 p (t-test) 0.46 0.057 0.72 Min 26.5 45.1 26.5 55.6 51.8 86.5 Max 5560 5840 3430 6840 5560 5840 n (Samp) 77 34 29 10 61 24 n (Patient) 77 34 29 10 61 24 At Enrollment sCr or UO sCr only UO only AUC 0.62 0.69 0.59 SE 0.059 0.10 0.070 p 0.051 0.065 0.18 nCohort 1 77 29 61 nCohort 2 34 10 24 Cutoff 1 210 285 233 Sens 1 71% 70% 71% Spec 1 52% 69% 51% Cutoff 2 123 166 168 Sens 2 82% 80% 83% Spec 2 26% 52% 36% Cutoff 3 95.2 85.3 104 Sens 3 91% 90% 92% Spec 3 19% 21% 18% Cutoff 4 303 487 318 Sens 4 44% 60% 38% Spec 4 70% 72% 70% Cutoff 5 471 700 471 Sens 5 35% 30% 25% Spec 5 81% 90% 80% Cutoff 6 1000 1240 1000 Sens 6 15% 30% 12% Spec 6 91% 93% 90% OR Quart 2 0.62 0.39 1.0 p Value 0.47 0.48 1.0 95% CI of 0.17 0.029 0.21 OR Quart2 2.3 5.2 4.7 OR Quart 3 1.6 1.5 3.2 p Value 0.43 0.70 0.10 95% CI of 0.50 0.19 0.79 OR Quart3 5.0 12 13 OR Quart 4 2.1 2.3 2.0 p Value 0.19 0.41 0.34 95% CI of 0.68 0.31 0.48 OR Quart4 6.7 18 8.1

TABLE 4 Comparison of the maximum marker levels in urine samples collected for Cohort 1 (patients that did not progress beyond RIFLE stage 0) and the maximum values in urine samples collected between enrollment and 0, 24 hours, and 48 hours prior to reaching stage F in Cohort 2. 0 hr prior to AKI stage 24 hr prior to AKI stage 48 hr prior to AKI stage sCr or UO Cohort 1 Cohort 2 Cohort 1 Cohort 2 Cohort 1 Cohort 2 Median 213 1200 213 700 213 595 Average 369 1840 369 1600 369 1440 Stdev 486 2000 486 1880 486 1990 p (t-test) 8.3E−15 6.2E−12 2.6E−7 Min 15.0 64.0 15.0 22.1 15.0 165 Max 4180 6840 4180 6840 4180 6840 n (Samp) 196 21 196 21 196 11 n (Patient) 196 21 196 21 196 11 0 hr prior to AKI stage 24 hr prior to AKI stage 48 hr prior to AKI stage sCr only Cohort 1 Cohort 2 Cohort 1 Cohort 2 Cohort 1 Cohort 2 Median 292 1240 292 700 292 707 Average 537 2090 537 2040 537 1870 Stdev 767 2240 767 2270 767 2510 p (t-test) 9.6E−9 3.1E−8 1.2E−4 Min 15.0 64.0 15.0 22.1 15.0 216 Max 5840 6840 5840 6840 5840 6840 n (Samp) 295 11 295 11 295 6 n (Patient) 295 11 295 11 295 6 0 hr prior to AKI stage 24 hr prior to AKI stage 48 hr prior to AKI stage UO only Cohort 1 Cohort 2 Cohort 1 Cohort 2 Cohort 1 Cohort 2 Median 224 814 224 700 224 504 Average 381 1950 381 1650 381 1450 Stdev 449 2240 449 2080 449 2210 p (t-test) 7.2E−11 1.3E−8 1.2E−5 Min 17.7 216 17.7 216 17.7 165 Max 3140 6840 3140 6840 3140 6840 n (Samp) 132 15 132 15 132 9 n (Patient) 132 15 132 15 132 9 0 hr prior to AKI stage 24 hr prior to AKI stage 48 hr prior to AKI stage sCr or UO sCr only UO only sCr or UO sCr only UO only sCr or UO sCr only UO only AUC 0.85 0.78 0.86 0.83 0.76 0.85 0.77 0.79 0.72 SE 0.054 0.083 0.063 0.056 0.085 0.064 0.084 0.11 0.099 p 9.0E−11 7.7E−4 1.5E−8 1.9E−9 0.0019 6.7E−8 0.0012 0.0093 0.026 nCohort 1 196 295 132 196 295 132 196 295 132 nCohort 2 21 11 15 21 11 15 11 6 9 Cutoff 1 691 698 691 691 698 691 346 698 238 Sens 1 76% 82% 73% 76% 82% 73% 73%  83%  78% Spec 1 83% 75% 83% 83% 75% 83% 68%  75%  54% Cutoff 2 570 698 570 570 698 570 244 698 211 Sens 2 81% 82% 80% 81% 82% 80% 82%  83%  89% Spec 2 80% 75% 80% 80% 75% 80% 57%  75%  48% Cutoff 3 244 211 238 244 211 238 211 211 165 Sens 3 90% 91% 93% 90% 91% 93% 91% 100% 100% Spec 3 57% 38% 54% 57% 38% 54% 50%  38%  33% Cutoff 4 369 521 400 369 521 400 369 521 400 Sens 4 81% 82% 80% 81% 82% 80% 64%  83%  56% Spec 4 70% 70% 70% 70% 70% 70% 70%  70%  70% Cutoff 5 570 700 604 570 700 604 570 700 604 Sens 5 81% 55% 73% 81% 45% 73% 55%  50%  33% Spec 5 80% 82% 80% 80% 82% 80% 80%  82%  80% Cutoff 6 700 1240 700 700 1240 700 700 1240 700 Sens 6 57% 45% 53% 48% 45% 47% 45%  33%  33% Spec 6 91% 92% 91% 91% 92% 91% 91%  92%  91% OR Quart 2 1.0 0.99 >2.1 1.0 0.99 >2.1 >2.0 >1.0 >2.1 p Value 1.0 0.99 <0.56 1.0 0.99 <0.56 <0.57 <0.99 <0.55 95% CI of 0.061 0.061 >0.18 0.061 0.061 >0.18 >0.18 >0.062 >0.18 OR Quart2 16 16 na 16 16 na na na na OR Quart 3 3.1 1.0 >2.1 3.1 3.1 >2.1 >2.0 >0 >3.3 p Value 0.33 1.0 <0.56 0.33 0.33 <0.56 <0.57 <na <0.31 95% CI of 0.31 0.061 >0.18 0.31 0.31 >0.18 >0.18 >na >0.32 OR Quart3 31 16 na 31 30 na na na na OR Quart 4 22 8.7 >15 22 6.3 >15 >7.9 >5.3 >4.4 p Value 0.0034 0.044 <0.011 0.0034 0.091 <0.011 <0.057 <0.13 <0.20 95% CI of 2.8 1.1 >1.8 2.8 0.74 >1.8 >0.94 >0.60 >0.46 OR Quart4 170 71 na 170 54 na na na na

TABLE 5 Comparison of marker levels in EDTA samples collected for Cohort 1 (patients that did not progress beyond RIFLE stage 0) and in EDTA samples collected from subjects at 0, 24 hours, and 48 hours prior to reaching stage R, I or F in Cohort 2. 0 hr prior to AKI stage 24 hr prior to AKI stage 48 hr prior to AKI stage sCr or UO Cohort 1 Cohort 2 Cohort 1 Cohort 2 Cohort 1 Cohort 2 Median 109000 112000 109000 101000 109000 98000 Average 120000 121000 120000 100000 120000 106000 Stdev 47100 36800 47100 41400 47100 54800 p (t-test) 0.89 0.011 0.19 Min 35700 55700 35700 24700 35700 48100 Max 292000 225000 292000 237000 292000 284000 n (Samp) 105 45 105 50 105 24 n (Patient) 97 45 97 50 97 24 0 hr prior to AKI stage 24 hr prior to AKI stage 48 hr prior to AKI stage sCr only Cohort 1 Cohort 2 Cohort 1 Cohort 2 Cohort 1 Cohort 2 Median 109000 106000 109000 104000 109000 130000 Average 116000 117000 116000 135000 116000 118000 Stdev 48700 32000 48700 145000 48700 53900 p (t-test) 0.94 0.22 0.89 Min 659 74200 659 40900 659 54800 Max 296000 179000 296000 658000 296000 219000 n (Samp) 246 13 246 16 246 11 n (Patient) 160 13 160 16 160 11 0 hr prior to AKI stage 24 hr prior to AKI stage 48 hr prior to AKI stage UO only Cohort 1 Cohort 2 Cohort 1 Cohort 2 Cohort 1 Cohort 2 Median 107000 129000 107000 101000 107000 97400 Average 115000 126000 115000 103000 115000 106000 Stdev 44300 42200 44300 42300 44300 54300 p (t-test) 0.21 0.13 0.38 Min 35700 52500 35700 24700 35700 48100 Max 243000 230000 243000 237000 243000 284000 n (Samp) 96 40 96 44 96 21 n (Patient) 84 40 84 44 84 21 0 hr prior to AKI stage 24 hr prior to AKI stage 48 hr prior to AKI stage sCr or UO sCr only UO only sCr or UO sCr only UO only sCr or UO sCr only UO only AUC 0.53 0.53 0.57 0.38 0.45 0.42 0.39 0.52 0.41 SE 0.052 0.084 0.055 0.049 0.076 0.053 0.066 0.090 0.071 p 0.61 0.70 0.18 0.013 0.53 0.13 0.094 0.87 0.20 nCohort 1 105 246 96 105 246 96 105 246 96 nCohort 2 45 13 40 50 16 44 24 11 21 Cutoff 1 100000 100000 101000 78900 78900 79600 63000 64500 76100 Sens 1 71% 77% 70% 70% 75% 70% 71% 73% 71% Spec 1 40% 42% 43% 19% 22% 25%  8% 13% 22% Cutoff 2 86000 98600 86000 61200 60500 62000 54800 60500 60500 Sens 2 80% 85% 80% 80% 81% 82% 83% 82% 81% Spec 2 24% 40% 29%  7% 11%  9%  2% 11%  9% Cutoff 3 74200 77000 74200 52000 40900 56000 50700 54800 52000 Sens 3 91% 92% 90% 90% 94% 91% 92% 91% 90% Spec 3 14% 22% 20%  2%  2%  4%  2%  6%  3% Cutoff 4 142000 137000 142000 142000 137000 142000 142000 137000 142000 Sens 4 29% 31% 35% 14% 25% 16% 12% 45% 10% Spec 4 70% 70% 71% 70% 70% 71% 70% 70% 71% Cutoff 5 157000 150000 157000 157000 150000 157000 157000 150000 157000 Sens 5 16% 23% 20%  4% 12%  7% 12% 18% 10% Spec 5 80% 80% 80% 80% 80% 80% 80% 80% 80% Cutoff 6 175000 170000 174000 175000 170000 174000 175000 170000 174000 Sens 6  7%  8% 10%  4%  6%  7%  8%  9% 10% Spec 6 90% 90% 91% 90% 90% 91% 90% 90% 91% OR Quart 2 1.2 3.2 1.6 2.3 1.4 2.1 3.3 0 4.5 p Value 0.67 0.17 0.40 0.12 0.68 0.18 0.099 na 0.079 95% CI of 0.46 0.61 0.53 0.80 0.30 0.71 0.80 na 0.84 OR Quart2 3.4 16 4.9 6.6 6.4 6.2 14 na 24 OR Quart 3 1.3 0.98 1.8 2.3 1.4 2.4 1.0 0.74 2.9 p Value 0.61 0.99 0.27 0.12 0.70 0.12 0.97 0.70 0.22 95% CI of 0.48 0.13 0.61 0.80 0.29 0.81 0.19 0.16 0.52 OR Quart3 3.5 7.2 5.5 6.6 6.3 6.9 5.5 3.4 16 OR Quart 4 1.1 1.5 2.1 3.7 1.8 2.1 4.5 0.98 4.5 p Value 0.85 0.66 0.18 0.013 0.46 0.18 0.034 0.98 0.079 95% CI of 0.40 0.24 0.71 1.3 0.40 0.71 1.1 0.24 0.84 OR Quart4 3.0 9.3 6.3 10 7.6 6.2 18 4.1 24

TABLE 6 Comparison of marker levels in EDTA samples collected for Cohort 1 (patients that did not progress beyond RIFLE stage 0 or R) and in EDTA samples collected from subjects at 0, 24 hours, and 48 hours prior to reaching stage I or F in Cohort 2. 0 hr prior to AKI stage 24 hr prior to AKI stage 48 hr prior to AKI stage sCr or UO Cohort 1 Cohort 2 Cohort 1 Cohort 2 Cohort 1 Cohort 2 Median 109000 118000 109000 104000 109000 62700 Average 121000 126000 121000 108000 121000 86200 Stdev 59900 38400 59900 46100 59900 51500 p (t-test) 0.72 0.27 0.028 Min 24700 52500 24700 40900 24700 659 Max 658000 229000 658000 219000 658000 190000 n (Samp) 230 19 230 26 230 15 n (Patient) 158 19 158 26 158 15 0 hr prior to AKI stage 24 hr prior to AKI stage 48 hr prior to AKI stage UO only Cohort 1 Cohort 2 Cohort 1 Cohort 2 Cohort 1 Cohort 2 Median 107000 118000 107000 104000 107000 88900 Average 120000 125000 120000 107000 120000 91500 Stdev 68900 40100 68900 45900 68900 52200 p (t-test) 0.79 0.36 0.13 Min 24700 61300 24700 46600 24700 659 Max 658000 229000 658000 219000 658000 190000 n (Samp) 201 19 201 26 201 14 n (Patient) 133 19 133 26 133 14 0 hr prior to AKI stage 24 hr prior to AKI stage 48 hr prior to AKI stage sCr or UO sCr only UO only sCr or UO sCr only UO only sCr or UO sCr only UO only AUC 0.58 nd 0.58 0.43 nd 0.45 0.29 nd 0.36 SE 0.071 nd 0.071 0.061 nd 0.062 0.077 nd 0.082 p 0.26 nd 0.24 0.28 nd 0.38 0.0075 nd 0.081 nCohort 1 230 nd 201 230 nd 201 230 nd 201 nCohort 2 19 nd 19 26 nd 26 15 nd 14 Cutoff 1 102000 nd 101000 72900 nd 72900 55800 nd 56000 Sens 1 74% nd 74% 73% nd 73% 73% nd 71% Spec 1 41% nd 44% 14% nd 17%  4% nd  7% Cutoff 2 100000 nd 99800 63000 nd 63000 55700 nd 55700 Sens 2 84% nd 84% 81% nd 81% 80% nd 86% Spec 2 40% nd 44%  9% nd 11%  4% nd  6% Cutoff 3 94600 nd 61300 50700 nd 52000 38400 nd 41800 Sens 3 95% nd 95% 92% nd 92% 93% nd 93% Spec 3 35% nd 10%  3% nd  4%  2% nd  3% Cutoff 4 140000 nd 137000 140000 nd 137000 140000 nd 137000 Sens 4 32% nd 32% 27% nd 31% 13% nd 14% Spec 4 70% nd 70% 70% nd 70% 70% nd 70% Cutoff 5 151000 nd 150000 151000 nd 150000 151000 nd 150000 Sens 5 32% nd 32% 15% nd 15% 13% nd 14% Spec 5 80% nd 80% 80% nd 80% 80% nd 80% Cutoff 6 175000 nd 175000 175000 nd 175000 175000 nd 175000 Sens 6  5% nd  5%  8% nd  8% 13% nd 14% Spec 6 90% nd 90% 90% nd 90% 90% nd 90% OR Quart 2 9.0 nd 2.6 1.2 nd 1.0 1.6 nd 1.5 p Value 0.041 nd 0.26 0.75 nd 1.0 0.64 nd 0.65 95% CI of 1.1 nd 0.49 0.35 nd 0.30 0.25 nd 0.25 OR Quart2 75 nd 14 4.2 nd 3.3 9.6 nd 9.5 OR Quart 3 4.2 nd 3.2 1.0 nd 0.82 0.50 nd 1.5 p Value 0.20 nd 0.16 1.0 nd 0.75 0.58 nd 0.65 95% CI of 0.46 nd 0.63 0.27 nd 0.23 0.044 nd 0.25 OR Quart3 39 nd 17 3.6 nd 2.8 5.7 nd 9.5 OR Quart 4 6.4 nd 3.2 2.2 nd 1.6 5.2 nd 3.3 p Value 0.090 nd 0.16 0.18 nd 0.39 0.041 nd 0.15 95% CI of 0.75 nd 0.63 0.70 nd 0.54 1.1 nd 0.64 OR Quart4 55 nd 17 6.8 nd 4.9 25 nd 17

TABLE 7 Comparison of marker levels in EDTA samples collected within 12 hours of reaching stage R for Cohort 1 (patients that reached, but did not progress beyond, RIFLE stage R) and for Cohort 2 (patients that reached RIFLE stage I or F). sCr or UO sCr only UO only Cohort 1 Cohort 2 Cohort 1 Cohort 2 Cohort 1 Cohort 2 Median 115000 101000 nd nd 128000 97100 Average 132000 121000 nd nd 149000 94300 Stdev 89100 116000 nd nd 117000 49300 p (t-test) 0.68 nd nd 0.097 Min 55700 659 nd nd 55700 659 Max 658000 567000 nd nd 658000 190000 n (Samp) 50 19 nd nd 41 14 n (Patient) 50 19 nd nd 41 14 At Enrollment sCr or UO sCr only UO only AUC 0.38 nd 0.31 SE 0.078 nd 0.087 p 0.13 nd 0.033 nCohort 1 50 nd 41 nCohort 2 19 nd 14 Cutoff 1 77300 nd 61000 Sens 1 74% nd 71% Spec 1 20% nd  7% Cutoff 2 61000 nd 50800 Sens 2 84% nd 86% Spec 2  8% nd  0% Cutoff 3 659 nd 659 Sens 3 95% nd 93% Spec 3  0% nd  0% Cutoff 4 141000 nd 146000 Sens 4 21% nd 14% Spec 4 72% nd 71% Cutoff 5 150000 nd 154000 Sens 5 16% nd  7% Spec 5 80% nd 80% Cutoff 6 179000 nd 225000 Sens 6 11% nd  0% Spec 6 90% nd 90% OR Quart 2 0.75 nd 1.0 p Value 0.74 nd 1.0 95% CI of 0.14 nd 0.12 OR Quart2 4.0 nd 8.3 OR Quart 3 1.5 nd 2.4 p Value 0.63 nd 0.36 95% CI of 0.32 nd 0.36 OR Quart3 6.7 nd 16 OR Quart 4 2.4 nd 5.1 p Value 0.23 nd 0.083 95% CI of 0.56 nd 0.81 OR Quart4 11 nd 33

TABLE 8 Comparison of the maximum marker levels in EDTA samples collected for Cohort 1 (patients that did not progress beyond RIFLE stage 0) and the maximum values in EDTA samples collected between enrollment and 0, 24 hours, and 48 hours prior to reaching stage F in Cohort 2. 0 hr prior to AKI stage 24 hr prior to AKI stage 48 hr prior to AKI stage sCr or UO Cohort 1 Cohort 2 Cohort 1 Cohort 2 Cohort 1 Cohort 2 Median 110000 100000 110000 93400 110000 107000 Average 122000 106000 122000 101000 122000 122000 Stdev 48000 54500 48000 53300 48000 55500 p (t-test) 0.32 0.21 0.99 Min 35700 46600 35700 46600 35700 55800 Max 292000 219000 292000 219000 292000 219000 n (Samp) 97 11 97 10 97 6 n (Patient) 97 11 97 10 97 6 0 hr prior to AKI stage 24 hr prior to AKI stage 48 hr prior to AKI stage UO only Cohort 1 Cohort 2 Cohort 1 Cohort 2 Cohort 1 Cohort 2 Median 109000 121000 109000 106000 109000 107000 Average 119000 122000 119000 110000 119000 122000 Stdev 45400 54900 45400 56200 45400 55500 p (t-test) 0.82 0.60 0.86 Min 35700 46600 35700 46600 35700 55800 Max 243000 219000 243000 219000 243000 219000 n (Samp) 84 8 84 8 84 6 n (Patient) 84 8 84 8 84 6 0 hr prior to AKI stage 24 hr prior to AKI stage 48 hr prior to AKI stage sCr or UO sCr only UO only sCr or UO sCr only UO only sCr or UO sCr only UO only AUC 0.40 nd 0.52 0.36 nd 0.43 0.49 nd 0.50 SE 0.095 nd 0.11 0.099 nd 0.11 0.12 nd 0.12 p 0.29 nd 0.87 0.16 nd 0.51 0.94 nd 1.0 nCohort 1 97 nd 84 97 nd 84 97 nd 84 nCohort 2 11 nd 8 10 nd 8 6 nd 6 Cutoff 1 63000 nd 99600 63000 nd 63000 98300 nd 95400 Sens 1 73% nd  75% 70% nd  75%  83% nd  83% Spec 1  7% nd  38%  7% nd  10%  35% nd  37% Cutoff 2 48900 nd 63000 60500 nd 60500 98300 nd 95400 Sens 2 82% nd  88% 80% nd  88%  83% nd  83% Spec 2  2% nd  10%  6% nd  8%  35% nd  37% Cutoff 3 46600 nd 38400 46600 nd 38400 38400 nd 38400 Sens 3 91% nd 100% 90% nd 100% 100% nd 100% Spec 3  2% nd  2%  2% nd  2%  2% nd  2% Cutoff 4 144000 nd 144000 144000 nd 144000 144000 nd 144000 Sens 4 27% nd  38% 20% nd  25%  33% nd  33% Spec 4 70% nd  70% 70% nd  70%  70% nd  70% Cutoff 5 164000 nd 164000 164000 nd 164000 164000 nd 164000 Sens 5  9% nd  12% 10% nd  12%  17% nd  17% Spec 5 84% nd  82% 84% nd  82%  84% nd  82% Cutoff 6 176000 nd 175000 176000 nd 175000 176000 nd 175000 Sens 6  9% nd  12% 10% nd  12%  17% nd  17% Spec 6 91% nd  90% 91% nd  90%  91% nd  90% OR Quart 2 1.6 nd 0.48 3.2 nd 3.3 2.1 nd 2.2 p Value 0.64 nd 0.56 0.32 nd 0.32 0.56 nd 0.53 95% CI of 0.24 nd 0.040 0.32 nd 0.32 0.18 nd 0.19 OR Quart2 10 nd 5.7 33 nd 34 25 nd 26 OR Quart 3 1.0 nd 1.6 2.1 nd 1.0 2.1 nd 2.1 p Value 1.0 nd 0.64 0.56 nd 1.0 0.56 nd 0.56 95% CI of 0.13 nd 0.24 0.18 nd 0.059 0.18 nd 0.18 OR Quart3 7.7 nd 10 24 nd 17 25 nd 25 OR Quart 4 2.2 nd 1.0 4.7 nd 3.3 1.0 nd 1.0 p Value 0.40 nd 1.0 0.18 nd 0.32 0.98 nd 0.97 95% CI of 0.36 nd 0.13 0.49 nd 0.32 0.062 nd 0.061 OR Quart4 13 nd 7.8 45 nd 34 18 nd 18

TABLE 9 Comparison of marker levels in urine samples collected from Cohort 1 (patients that did not progress beyond RIFLE stage 0, R, or I) and in urine samples collected from Cohort 2 (subjects who progress to RIFLE stage F) at 0, 24 hours, and 48 hours prior to the subject reaching RIFLE stage I. 0 hr prior to AKI stage 24 hr prior to AKI stage 48 hr prior to AKI stage sCr or UO Cohort 1 Cohort 2 Cohort 1 Cohort 2 Cohort 1 Cohort 2 Median 210 700 210 700 210 140 Average 400 900 400 1300 400 280 Stdev 760 1000 760 1500 760 270 p (t-test) 0.015 9.3E−6 0.70 Min 13 22 13 47 13 83 Max 15000 4000 15000 6200 15000 710 n (Samp) 932 14 932 15 932 6 n (Patient) 343 14 343 15 343 6 0 hr prior to AKI stage 24 hr prior to AKI stage 48 hr prior to AKI stage sCr only Cohort 1 Cohort 2 Cohort 1 Cohort 2 Cohort 1 Cohort 2 Median 210 550 nd nd nd nd Average 420 480 nd nd nd nd Stdev 790 280 nd nd nd nd p (t-test) 0.86 nd nd nd nd Min 13 22 nd nd nd nd Max 15000 700 nd nd nd nd n (Samp) 967 6 nd nd nd nd n (Patient) 353 6 nd nd nd nd 0 hr prior to AKI stage 24 hr prior to AKI stage 48 hr prior to AKI stage UO only Cohort 1 Cohort 2 Cohort 1 Cohort 2 Cohort 1 Cohort 2 Median 230 700 230 700 nd nd Average 400 790 400 1300 nd nd Stdev 560 550 560 1600 nd nd p (t-test) 0.036 1.8E−8 nd nd Min 13 42 13 47 nd nd Max 6000 1700 6000 6200 nd nd n (Samp) 768 9 768 13 nd nd n (Patient) 252 9 252 13 nd nd 0 hr prior to AKI stage 24 hr prior to AKI stage 48 hr prior to AKI stage sCr or UO sCr only UO only sCr or UO sCr only UO only sCr or UO sCr only UO only AUC 0.70 0.66 0.72 0.81 nd 0.79 0.44 nd nd SE 0.079 0.12 0.097 0.068 nd 0.075 0.12 nd nd p 0.010 0.19 0.024 3.6E−6 nd 1.1E−4 0.64 nd nd nCohort 1 932 967 768 932 nd 768 932 nd nd nCohort 2 14 6 9 15 nd 13 6 nd nd Cutoff 1 400 330 560 700 nd 700 100 nd nd Sens 1 71%  83%  78% 80% nd 77%  83% nd nd Spec 1 73%  68%  78% 83% nd 82%  21% nd nd Cutoff 2 110 330 110 700 nd 580 100 nd nd Sens 2 86%  83%  89% 80% nd 85%  83% nd nd Spec 2 24%  68%  21% 83% nd 79%  21% nd nd Cutoff 3 41 20 41 130 nd 130 83 nd nd Sens 3 93% 100% 100% 93% nd 92% 100% nd nd Spec 3  4%  1%  4% 29% nd 27%  15% nd nd Cutoff 4 350 360 370 350 nd 370 350 nd nd Sens 4 71%  67%  78% 87% nd 85%  33% nd nd Spec 4 70%  70%  70% 70% nd 70%  70% nd nd Cutoff 5 570 640 630 570 nd 630 570 nd nd Sens 5 57%  50%  67% 87% nd 77%  17% nd nd Spec 5 80%  80%  80% 80% nd 80%  80% nd nd Cutoff 6 740 800 780 740 nd 780 740 nd nd Sens 6 29%  0%  33% 47% nd 46%  0% nd nd Spec 6 90%  90%  90% 90% nd 90%  90% nd nd OR Quart 2 0 0 0 1.00 nd 1.0 0 nd nd p Value na na na 1.00 nd 1.0 na nd nd 95% CI of na na na 0.062 nd 0.062 na nd nd OR Quart2 na na na 16 nd 16 na nd nd OR Quart 3 0.66 2.0 0 0 nd 0 0.50 nd nd p Value 0.66 0.57 na na nd na 0.57 nd nd 95% CI of 0.11 0.18 na na nd na 0.045 nd nd OR Quart3 4.0 22 na na nd na 5.5 nd nd OR Quart 4 3.1 3.0 3.6 14 nd 12 1.5 nd nd p Value 0.096 0.34 0.12 0.012 nd 0.020 0.65 nd nd 95% CI of 0.82 0.31 0.73 1.8 nd 1.5 0.25 nd nd OR Quart4 11 29 17 110 nd 90 9.1 nd nd

TABLE 10 Comparison of marker levels in EDTA samples collected from Cohort 1 (patients that did not progress beyond RIFLE stage 0, R, or I) and in EDTA samples collected from Cohort 2 (subjects who progress to RIFLE stage F) at 0, 24 hours, and 48 hours prior to the subject reaching RIFLE stage I. 0 hr prior to AKI stage 24 hr prior to AKI stage 48 hr prior to AKI stage sCr or UO Cohort 1 Cohort 2 Cohort 1 Cohort 2 Cohort 1 Cohort 2 Median 110000 100000 110000 89000 nd nd Average 120000 97000 120000 110000 nd nd Stdev 63000 40000 63000 66000 nd nd p (t-test) 0.36 0.68 nd nd Min 660 49000 660 47000 nd nd Max 660000 160000 660000 220000 nd nd n (Samp) 306 7 306 6 nd nd n (Patient) 190 7 190 6 nd nd 0 hr prior to AKI stage 24 hr prior to AKI stage 48 hr prior to AKI stage UO only Cohort 1 Cohort 2 Cohort 1 Cohort 2 Cohort 1 Cohort 2 Median nd nd 110000 89000 nd nd Average nd nd 120000 110000 nd nd Stdev nd nd 64000 66000 nd nd p (t-test) nd nd 0.73 nd nd Min nd nd 660 47000 nd nd Max nd nd 660000 220000 nd nd n (Samp) nd nd 269 6 nd nd n (Patient) nd nd 161 6 nd nd 0 hr prior to AKI stage 24 hr prior to AKI stage 48 hr prior to AKI stage sCr or UO sCr only UO only sCr or UO sCr only UO only sCr or UO sCr only UO only AUC 0.39 nd nd 0.42 nd 0.43 nd nd nd SE 0.11 nd nd 0.12 nd 0.12 nd nd nd p 0.32 nd nd 0.52 nd 0.56 nd nd nd nCohort 1 306 nd nd 306 nd 269 nd nd nd nCohort 2 7 nd nd 6 nd 6 nd nd nd Cutoff 1 88000 nd nd 61000 nd 61000 nd nd nd Sens 1  71% nd nd  83% nd  83% nd nd nd Spec 1  29% nd nd  11% nd  12% nd nd nd Cutoff 2 52000 nd nd 61000 nd 61000 nd nd nd Sens 2  86% nd nd  83% nd  83% nd nd nd Spec 2  6% nd nd  11% nd  12% nd nd nd Cutoff 3 48000 nd nd 45000 nd 45000 nd nd nd Sens 3 100% nd nd 100% nd 100% nd nd nd Spec 3  4% nd nd  4% nd  4% nd nd nd Cutoff 4 140000 nd nd 140000 nd 140000 nd nd nd Sens 4  14% nd nd  33% nd  33% nd nd nd Spec 4  70% nd nd  70% nd  70% nd nd nd Cutoff 5 150000 nd nd 150000 nd 150000 nd nd nd Sens 5  14% nd nd  17% nd  17% nd nd nd Spec 5  80% nd nd  80% nd  80% nd nd nd Cutoff 6 170000 nd nd 170000 nd 170000 nd nd nd Sens 6  0% nd nd  17% nd  17% nd nd nd Spec 6  90% nd nd  90% nd  90% nd nd nd OR Quart 2 1.0 nd nd 2.0 nd 2.0 nd nd nd p Value 0.99 nd nd 0.57 nd 0.57 nd nd nd 95% CI of 0.062 nd nd 0.18 nd 0.18 nd nd nd OR Quart2 16 nd nd 23 nd 23 nd nd nd OR Quart 3 3.1 nd nd 0 nd 0 nd nd nd p Value 0.33 nd nd na nd na nd nd nd 95% CI of 0.32 nd nd na nd na nd nd nd OR Quart3 31 nd nd na nd na nd nd nd OR Quart 4 2.1 nd nd 3.1 nd 3.1 nd nd nd p Value 0.56 nd nd 0.33 nd 0.33 nd nd nd 95% CI of 0.18 nd nd 0.31 nd 0.32 nd nd nd OR Quart4 23 nd nd 30 nd 31 nd nd nd

TABLE 11 Comparison of marker levels in enroll urine samples collected for Cohort 1 (patients that did not progress beyond RIFLE stage 0 or R within 48 hrs) and in enroll urine samples collected from Cohort 2 (subjects reaching RIFLE stage I or F within 48 hrs). Enroll samples from patients already at RIFLE stage I or F were included in Cohort 2. sCr or UO sCr only UO only Cohort 1 Cohort 2 Cohort 1 Cohort 2 Cohort 1 Cohort 2 Median 200 700 210 700 200 700 Average 350 1300 450 2100 370 1100 Stdev 570 2300 780 4200 590 1400 p (t-test) 7.4E−9 2.6E−7 7.4E−8 Min 14 22 14 22 14 47 Max 6000 15000 6200 15000 6000 6200 n (Samp) 292 59 336 12 204 53 n (Patient) 292 59 336 12 204 53 At Enrollment sCr or UO sCr only UO only AUC 0.75 0.74 0.76 SE 0.039 0.083 0.041 p 8.6E−11 0.0039 3.7E−10 nCohort 1 292 336 204 nCohort 2 59 12 53 Cutoff 1 280 700 280 Sens 1 71% 83% 72% Spec 1 66% 81% 64% Cutoff 2 190 700 230 Sens 2 81% 83% 81% Spec 2 49% 81% 54% Cutoff 3 97 46 150 Sens 3 92% 92% 91% Spec 3 23%  6% 36% Cutoff 4 310 380 320 Sens 4 68% 83% 68% Spec 4 70% 70% 70% Cutoff 5 470 680 490 Sens 5 63% 83% 62% Spec 5 80% 80% 80% Cutoff 6 700 1000 700 Sens 6 37% 25% 40% Spec 6 92% 90% 93% OR Quart 2 0.69 0 1.4 p Value 0.54 na 0.55 95% CI of 0.21 na 0.43 OR Quart2 2.3 na 4.8 OR Quart 3 1.6 0 1.9 p Value 0.34 na 0.26 95% CI of 0.60 na 0.61 OR Quart3 4.4 na 6.1 OR Quart 4 7.9 5.5 11 p Value 4.3E−6 0.031 3.9E−6 95% CI of 3.3 1.2 4.1 OR Quart4 19 26 32

TABLE 12 Comparison of marker levels in enroll EDTA samples collected from Cohort 1 (patients that did not progress beyond RIFLE stage 0 or R within 48 hrs) and in enroll EDTA samples collected from Cohort 2 (subjects reaching RIFLE stage I or F within 48 hrs). Enroll samples from patients already at stage I or F were included in Cohort 2. sCr or UO sCr only UO only Cohort 1 Cohort 2 Cohort 1 Cohort 2 Cohort 1 Cohort 2 Median 110000 79000 nd nd 110000 79000 Average 120000 88000 nd nd 120000 90000 Stdev 88000 40000 nd nd 92000 40000 p (t-test) 0.087 nd nd 0.14 Min 660 47000 nd nd 660 47000 Max 660000 190000 nd nd 660000 190000 n (Samp) 95 23 nd nd 80 22 n (Patient) 95 23 nd nd 80 22 At Enrollment sCr or UO sCr only UO only AUC 0.34 nd 0.36 SE 0.067 nd 0.070 p 0.019 nd 0.052 nCohort 1 95 nd 80 nCohort 2 23 nd 22 Cutoff 1 57000 nd 59000 Sens 1 74% nd 73% Spec 1 12% nd 14% Cutoff 2 55000 nd 56000 Sens 2 83% nd 82% Spec 2  8% nd 10% Cutoff 3 48000 nd 49000 Sens 3 91% nd 91% Spec 3  5% nd  6% Cutoff 4 130000 nd 120000 Sens 4 22% nd 23% Spec 4 71% nd 70% Cutoff 5 150000 nd 150000 Sens 5  4% nd  5% Spec 5 80% nd 80% Cutoff 6 160000 nd 160000 Sens 6  4% nd  5% Spec 6 91% nd 90% OR Quart 2 0.75 nd 0.75 p Value 0.72 nd 0.73 95% CI of 0.15 nd 0.15 OR Quart2 3.7 nd 3.7 OR Quart 3 1.3 nd 1.3 p Value 0.72 nd 0.71 95% CI of 0.31 nd 0.31 OR Quart3 5.4 nd 5.6 OR Quart 4 4.0 nd 3.7 p Value 0.036 nd 0.056 95% CI of 1.1 nd 0.97 OR Quart4 14 nd 14

While the invention has been described and exemplified in sufficient detail for those skilled in this art to make and use it, various alternatives, modifications, and improvements should be apparent without departing from the spirit and scope of the invention. The examples provided herein are representative of preferred embodiments, are exemplary, and are not intended as limitations on the scope of the invention. Modifications therein and other uses will occur to those skilled in the art. These modifications are encompassed within the spirit of the invention and are defined by the scope of the claims.

It will be readily apparent to a person skilled in the art that varying substitutions and modifications may be made to the invention disclosed herein without departing from the scope and spirit of the invention.

All patents and publications mentioned in the specification are indicative of the levels of those of ordinary skill in the art to which the invention pertains. All patents and publications are herein incorporated by reference to the same extent as if each individual publication was specifically and individually indicated to be incorporated by reference.

The invention illustratively described herein suitably may be practiced in the absence of any element or elements, limitation or limitations which is not specifically disclosed herein. Thus, for example, in each instance herein any of the terms “comprising”, “consisting essentially of” and “consisting of” may be replaced with either of the other two terms. The terms and expressions which have been employed are used as terms of description and not of limitation, and there is no intention that in the use of such terms and expressions of excluding any equivalents of the features shown and described or portions thereof, but it is recognized that various modifications are possible within the scope of the invention claimed. Thus, it should be understood that although the present invention has been specifically disclosed by preferred embodiments and optional features, modification and variation of the concepts herein disclosed may be resorted to by those skilled in the art, and that such modifications and variations are considered to be within the scope of this invention as defined by the appended claims.

Other embodiments are set forth within the following claims. 

We claim:
 1. A method for evaluating renal status in a subject, comprising: performing an assay method configured to detect Beta-2-glycoprotein 1 by introducing a body fluid sample obtained from the subject into an assay instrument which (i) contacts all or a portion of the body fluid sample with a binding reagent which specifically binds for detection Beta-2-glycoprotein 1 and (ii) generates an assay result indicative of Beta-2-glycoprotein 1 binding to the binding reagent; correlating the assay result generated by the assay instrument to a likelihood that the renal function of the subject will improve within 72 hours of the time at which the body fluid sample is obtained from the subject by using the assay result to assign the subject to a predetermined subpopulation of individuals having a current acute renal injury and that have a known predisposition to the nonoccurrence of continued acute renal failure within 72 hours.
 2. A method according to claim 1, wherein said correlating step comprises correlating the assay result to a likelihood that the renal function of the subject will improve within 48 hours of the time at which the body fluid sample is obtained.
 3. A method according to claim 2, wherein said correlating step comprises correlating the assay result to a likelihood that the renal function of the subject will improve within 24 hours of the time at which the body fluid sample is obtained.
 4. A method according to claim 1, wherein the subject is in RIFLE stage I or F.
 5. A method according to claim 1, wherein said correlating step comprises correlating the assay result to a likelihood that the renal function of the subject will improve within 48 hours of the time at which the body fluid sample is obtained.
 6. A method according to claim 5, wherein said correlating step comprises correlating the assay result to a likelihood that the renal function of the subject will improve within 24 hours of the time at which the body fluid sample is obtained. 